downloading
Scotch and libScotch 5.1 User’s Guide
(version 5.1.1)
François Pellegrini
ScAlApplix project, INRIA Bordeaux Sud-Ouest
ENSEIRB & LaBRI, UMR CNRS 5800
Université Bordeaux I
351 cours de la Libération, 33405 TALENCE, FRANCE
[email protected]
October 14, 2008
Abstract
This document describes the capabilities and operations of Scotch and
libScotch, a software package and a software library devoted to static
mapping, partitioning, and sparse matrix block ordering of graphs and
meshes/hypergraphs. It gives brief descriptions of the algorithms, details
the input/output formats, instructions for use, installation procedures, and
provides a number of examples.
Scotch is distributed as free/libre software, and has been designed such
that new partitioning or ordering methods can be added in a straightforward
manner. It can therefore be used as a testbed for the easy and quick coding
and testing of such new methods, and may also be redistributed, as a library,
along with third-party software that makes use of it, either in its original or
in updated forms.
1
Contents
1 Introduction
1.1 Static mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.2 Sparse matrix ordering . . . . . . . . . . . . . . . . . . . . . . . . . .
1.3 Contents of this document . . . . . . . . . . . . . . . . . . . . . . . .
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2 The Scotch project
2.1 Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2 Availability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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3 Algorithms
3.1 Static mapping by Dual Recursive Bipartitioning . . . . . . . .
3.1.1 Static mapping . . . . . . . . . . . . . . . . . . . . . . .
3.1.2 Cost function and performance criteria . . . . . . . . . .
3.1.3 The Dual Recursive Bipartitioning algorithm . . . . . .
3.1.4 Partial cost function . . . . . . . . . . . . . . . . . . . .
3.1.5 Execution scheme . . . . . . . . . . . . . . . . . . . . .
3.1.6 Graph bipartitioning methods . . . . . . . . . . . . . . .
3.1.7 Mapping onto variable-sized architectures . . . . . . . .
3.2 Sparse matrix ordering by hybrid incomplete nested dissection
3.2.1 Minimum Degree . . . . . . . . . . . . . . . . . . . . . .
3.2.2 Nested dissection . . . . . . . . . . . . . . . . . . . . . .
3.2.3 Hybridization . . . . . . . . . . . . . . . . . . . . . . . .
3.2.4 Performance criteria . . . . . . . . . . . . . . . . . . . .
3.2.5 Ordering methods . . . . . . . . . . . . . . . . . . . . .
3.2.6 Graph separation methods . . . . . . . . . . . . . . . . .
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4 Updates
4.1 Changes from version 4.0 . . . . . . . . . . . . . . . . . . . . . . . .
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5 Files and data structures
5.1 Graph files . . . . . . . . . . . . . . . . . . . .
5.2 Mesh files . . . . . . . . . . . . . . . . . . . . .
5.3 Geometry files . . . . . . . . . . . . . . . . . .
5.4 Target files . . . . . . . . . . . . . . . . . . . .
5.4.1 Decomposition-defined architecture files
5.4.2 Algorithmically-coded architecture files
5.4.3 Variable-sized architecture files . . . . .
5.5 Mapping files . . . . . . . . . . . . . . . . . . .
5.6 Ordering files . . . . . . . . . . . . . . . . . . .
5.7 Vertex list files . . . . . . . . . . . . . . . . . .
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6 Programs
6.1 Invocation . . . .
6.2 Using compressed
6.3 Description . . .
6.3.1 acpl . . .
6.3.2 amk * . .
6.3.3 amk grf .
6.3.4 atst . . .
6.3.5 gcv . . .
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6.3.6
6.3.7
6.3.8
6.3.9
6.3.10
6.3.11
6.3.12
6.3.13
6.3.14
6.3.15
6.3.16
6.3.17
gmap . .
gmk * .
gmk msh
gmtst .
gord . .
gotst .
gout . .
gtst . .
mcv . .
mmk * .
mord . .
mtst . .
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7 Library
7.1 Calling the routines of libScotch . . . . .
7.1.1 Calling from C . . . . . . . . . . . .
7.1.2 Calling from Fortran . . . . . . . . .
7.1.3 Compiling and linking . . . . . . . .
7.1.4 Machine word size issues . . . . . . .
7.2 Data formats . . . . . . . . . . . . . . . . .
7.2.1 Architecture format . . . . . . . . .
7.2.2 Graph format . . . . . . . . . . . . .
7.2.3 Mesh format . . . . . . . . . . . . .
7.2.4 Geometry format . . . . . . . . . . .
7.2.5 Block ordering format . . . . . . . .
7.3 Strategy strings . . . . . . . . . . . . . . . .
7.3.1 Mapping strategy strings . . . . . .
7.3.2 Graph bipartitioning strategy strings
7.3.3 Ordering strategy strings . . . . . .
7.3.4 Node separation strategy strings . .
7.4 Target architecture handling routines . . . .
7.4.1 SCOTCH archInit . . . . . . . . . . .
7.4.2 SCOTCH archExit . . . . . . . . . . .
7.4.3 SCOTCH archLoad . . . . . . . . . . .
7.4.4 SCOTCH archSave . . . . . . . . . . .
7.4.5 SCOTCH archBuild . . . . . . . . . .
7.4.6 SCOTCH archCmplt . . . . . . . . . .
7.4.7 SCOTCH archCmpltw . . . . . . . . .
7.4.8 SCOTCH archName . . . . . . . . . . .
7.4.9 SCOTCH archSize . . . . . . . . . . .
7.5 Graph handling routines . . . . . . . . . . .
7.5.1 SCOTCH graphInit . . . . . . . . . .
7.5.2 SCOTCH graphExit . . . . . . . . . .
7.5.3 SCOTCH graphFree . . . . . . . . . .
7.5.4 SCOTCH graphLoad . . . . . . . . . .
7.5.5 SCOTCH graphSave . . . . . . . . . .
7.5.6 SCOTCH graphBuild . . . . . . . . .
7.5.7 SCOTCH graphBase . . . . . . . . . .
7.5.8 SCOTCH graphCheck . . . . . . . . .
7.5.9 SCOTCH graphSize . . . . . . . . . .
7.5.10 SCOTCH graphData . . . . . . . . . .
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7.5.11 SCOTCH graphStat . . . . . . . . .
Graph mapping and partitioning routines
7.6.1 SCOTCH graphPart . . . . . . . . .
7.6.2 SCOTCH graphMap . . . . . . . . . .
7.6.3 SCOTCH graphMapInit . . . . . . .
7.6.4 SCOTCH graphMapExit . . . . . . .
7.6.5 SCOTCH graphMapLoad . . . . . . .
7.6.6 SCOTCH graphMapSave . . . . . . .
7.6.7 SCOTCH graphMapCompute . . . . .
7.6.8 SCOTCH graphMapView . . . . . . .
7.7 Graph ordering routines . . . . . . . . . .
7.7.1 SCOTCH graphOrder . . . . . . . .
7.7.2 SCOTCH graphOrderInit . . . . . .
7.7.3 SCOTCH graphOrderExit . . . . . .
7.7.4 SCOTCH graphOrderLoad . . . . . .
7.7.5 SCOTCH graphOrderSave . . . . . .
7.7.6 SCOTCH graphOrderSaveMap . . .
7.7.7 SCOTCH graphOrderSaveTree . . .
7.7.8 SCOTCH graphOrderCheck . . . . .
7.7.9 SCOTCH graphOrderCompute . . .
7.7.10 SCOTCH graphOrderComputeList .
7.8 Mesh handling routines . . . . . . . . . .
7.8.1 SCOTCH meshInit . . . . . . . . . .
7.8.2 SCOTCH meshExit . . . . . . . . . .
7.8.3 SCOTCH meshLoad . . . . . . . . . .
7.8.4 SCOTCH meshSave . . . . . . . . . .
7.8.5 SCOTCH meshBuild . . . . . . . . .
7.8.6 SCOTCH meshCheck . . . . . . . . .
7.8.7 SCOTCH meshSize . . . . . . . . . .
7.8.8 SCOTCH meshData . . . . . . . . . .
7.8.9 SCOTCH meshStat . . . . . . . . . .
7.8.10 SCOTCH meshGraph . . . . . . . . .
7.9 Mesh ordering routines . . . . . . . . . . .
7.9.1 SCOTCH meshOrder . . . . . . . . .
7.9.2 SCOTCH meshOrderInit . . . . . .
7.9.3 SCOTCH meshOrderExit . . . . . .
7.9.4 SCOTCH meshOrderSave . . . . . .
7.9.5 SCOTCH meshOrderSaveMap . . . .
7.9.6 SCOTCH meshOrderSaveTree . . .
7.9.7 SCOTCH meshOrderCheck . . . . . .
7.9.8 SCOTCH meshOrderCompute . . . .
7.10 Strategy handling routines . . . . . . . . .
7.10.1 SCOTCH stratInit . . . . . . . . .
7.10.2 SCOTCH stratExit . . . . . . . . .
7.10.3 SCOTCH stratSave . . . . . . . . .
7.10.4 SCOTCH stratGraphBipart . . . .
7.10.5 SCOTCH stratGraphMap . . . . . .
7.10.6 SCOTCH stratGraphOrder . . . . .
7.10.7 SCOTCH stratMeshOrder . . . . . .
7.11 Geometry handling routines . . . . . . . .
7.11.1 SCOTCH geomInit . . . . . . . . . .
7.6
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7.11.2 SCOTCH geomExit . . . . . . .
7.11.3 SCOTCH geomData . . . . . . .
7.11.4 SCOTCH graphGeomLoadChac
7.11.5 SCOTCH graphGeomSaveChac
7.11.6 SCOTCH graphGeomLoadHabo
7.11.7 SCOTCH graphGeomLoadScot
7.11.8 SCOTCH graphGeomSaveScot
7.11.9 SCOTCH meshGeomLoadHabo .
7.11.10 SCOTCH meshGeomLoadScot .
7.11.11 SCOTCH meshGeomSaveScot .
7.12 Error handling routines . . . . . . .
7.12.1 SCOTCH errorPrint . . . . .
7.12.2 SCOTCH errorPrintW . . . . .
7.12.3 SCOTCH errorProg . . . . . .
7.13 Miscellaneous routines . . . . . . . .
7.13.1 SCOTCH randomReset . . . . .
7.14 MeTiS compatibility library . . . . .
7.14.1 METIS EdgeND . . . . . . . . .
7.14.2 METIS NodeND . . . . . . . . .
7.14.3 METIS NodeWND . . . . . . . .
7.14.4 METIS PartGraphKway . . . .
7.14.5 METIS PartGraphRecursive
7.14.6 METIS PartGraphVKway . . .
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8 Installation
117
9 Examples
118
10 Adding new features to Scotch
10.1 Graphs and meshes . . . . . . . . . . . .
10.2 Methods and partition data . . . . . . .
10.3 Adding a new method to Scotch . . .
10.4 Licensing of new methods and of derived
1
1.1
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120
120
121
121
123
Introduction
Static mapping
The efficient execution of a parallel program on a parallel machine requires that
the communicating processes of the program be assigned to the processors of the
machine so as to minimize its overall running time. When processes have a limited duration and their logical dependencies are accounted for, this optimization
problem is referred to as scheduling. When processes are assumed to coexist simultaneously for the entire duration of the program, it is referred to as mapping. It
amounts to balancing the computational weight of the processes among the processors of the machine, while reducing the cost of communication by keeping intensively
inter-communicating processes on nearby processors. In most cases, the underlying
computational structure of the parallel programs to map can be conveniently modeled as a graph in which vertices correspond to processes that handle distributed
pieces of data, and edges reflect data dependencies. The mapping problem can then
be addressed by assigning processor labels to the vertices of the graph, so that all
5
processes assigned to some processor are loaded and run on it. In a SPMD context, this is equivalent to the distribution across processors of the data structures
of parallel programs; in this case, all pieces of data assigned to some processor are
handled by a single process located on this processor.
A mapping is called static if it is computed prior to the execution of the program.
Static mapping is NP-complete in the general case [13]. Therefore, many studies
have been carried out in order to find sub-optimal solutions in reasonable time,
including the development of specific algorithms for common topologies such as the
hypercube [11, 21]. When the target machine is assumed to have a communication
network in the shape of a complete graph, the static mapping problem turns into the
partitioning problem, which has also been intensely studied [4, 22, 31, 33, 51]. However, when mapping onto parallel machines the communication network of which is
not a bus, not accounting for the topology of the target machine usually leads to
worse running times, because simple cut minimization can induce more expensive
long-distance communication [21, 58].
1.2
Sparse matrix ordering
Many scientific and engineering problems can be modeled by sparse linear systems,
which are solved either by iterative or direct methods. To achieve efficiency with
direct methods, one must minimize the fill-in induced by factorization. This fill-in
is a direct consequence of the order in which the unknowns of the linear system are
numbered, and its effects are critical both in terms of memory and computation
costs.
An efficient way to compute fill reducing orderings of symmetric sparse matrices
is to use recursive nested dissection [17]. It amounts to computing a vertex set S
that separates the graph into two parts A and B, ordering S with the highest indices
that are still available, and proceeding recursively on parts A and B until their sizes
become smaller than some threshold value. This ordering guarantees that, at each
step, no non-zero term can appear in the factorization process between unknowns
of A and unknowns of B.
The main issue of the nested dissection ordering algorithm is thus to find small
vertex separators that balance the remaining subgraphs as evenly as possible, in
order to minimize fill-in and to increase concurrency in the factorization process.
1.3
Contents of this document
This document describes the capabilities and operations of Scotch, a software
package devoted to static mapping, graph and mesh partitioning, and sparse matrix
block ordering. Scotch allows the user to map efficiently any kind of weighted
process graph onto any kind of weighted architecture graph, and provides highquality block orderings of sparse matrices. The rest of this manual is organized
as follows. Section 2 presents the goals of the Scotch project, and section 3
outlines the most important aspects of the mapping and ordering algorithms that it
implements. Section 4 summarizes the most important changes between version 5.0
and previous versions. Section 5 defines the formats of the files used in Scotch,
section 6 describes the programs of the Scotch distribution, and section 7 defines
the interface and operations of the libScotch library. Section 8 explains how
to obtain and install the Scotch distribution. Finally, some practical examples
are given in section 9, and instructions on how to implement new methods in the
libScotch library are provided in section 10.
6
2
2.1
The Scotch project
Description
Scotch is a project carried out at the Laboratoire Bordelais de Recherche en Informatique (LaBRI) of the Université Bordeaux I, and now within the ScAlApplix
project of INRIA Bordeaux Sud-Ouest. Its goal is to study the applications of graph
theory to scientific computing, using a “divide and conquer” approach.
It focused first on static mapping, and has resulted in the development of the
Dual Recursive Bipartitioning (or DRB) mapping algorithm and in the study of
several graph bipartitioning heuristics [43], all of which have been implemented in
the Scotch software package [47]. Then, it focused on the computation of highquality vertex separators for the ordering of sparse matrices by nested dissection,
by extending the work that has been done on graph partitioning in the context
of static mapping [48, 49]. More recently, the ordering capabilities of Scotch
have been extended to native mesh structures, thanks to hypergraph partitioning
algorithms. New graph partitioning methods have also been recently added [8, 44].
Version 5.0 of Scotch is the first one to comprise parallel graph ordering routines. The parallel features of Scotch are referred to as PT-Scotch (“Parallel
Threaded Scotch”). While both packages share a significant amount of code, beacuse PT-Scotch transfers control to the sequential routines of the libScotch
library when the subgraphs on which it operates are located on a single processor,
the two sets of routines have a distinct user’s manual. Readers interested in the
parallel features of Scotch should refer to the PT-Scotch 5.1 User’s Guide [45].
2.2
Availability
Starting from version 4.0, which has been developed at INRIA within the ScAlApplix project, Scotch is available under a dual licensing basis. On the one hand, it
is downloadable from the Scotch web page as free/libre software, to all interested
parties willing to use it as a library or to contribute to it as a testbed for new
partitioning and ordering methods. On the other hand, it can also be distributed,
under other types of licenses and conditions, to parties willing to embed it tightly
into closed, proprietary software.
The free/libre software license under which Scotch 5.1 is distributed is
the CeCILL-C license [6], which has basically the same features as the GNU
LGPL (“Lesser General Public License”): ability to link the code as a library
to any free/libre or even proprietary software, ability to modify the code and to
redistribute these modifications. Version 4.0 of Scotch was distributed under the
LGPL itself.
Please refer to section 8 to see how to obtain the free/libre distribution of
Scotch.
3
3.1
Algorithms
Static mapping by Dual Recursive Bipartitioning
For a detailed description of the mapping algorithm and an extensive analysis of its
performance, please refer to [43, 46]. In the next sections, we will only outline the
most important aspects of the algorithm.
7
3.1.1
Static mapping
The parallel program to be mapped onto the target architecture is modeled by a valuated unoriented graph S called source graph or process graph, the vertices of which
represent the processes of the parallel program, and the edges of which the communication channels between communicating processes. Vertex- and edge- valuations
associate with every vertex vS and every edge eS of S integer numbers wS (vS ) and
wS (eS ) which estimate the computation weight of the corresponding process and
the amount of communication to be transmitted on the channel, respectively.
The target machine onto which is mapped the parallel program is also modeled
by a valuated unoriented graph T called target graph or architecture graph. Vertices
vT and edges eT of T are assigned integer weights wT (vT ) and wT (eT ), which
estimate the computational power of the corresponding processor and the cost of
traversal of the inter-processor link, respectively.
A mapping from S to T consists of two applications τS,T : V (S) −→ V (T ) and
ρS,T : E(S) −→ P(E(T )), where P(E(T )) denotes the set of all simple loopless
paths which can be built from E(T ). τS,T (vS ) = vT if process vS of S is mapped
onto processor vT of T , and ρS,T (eS ) = {e1T , e2T , . . . , enT } if communication channel
eS of S is routed through communication links e1T , e2T , . . . , enT of T . |ρS,T (eS )|
denotes the dilation of edge eS , that is, the number of edges of E(T ) used to route
eS .
3.1.2
Cost function and performance criteria
The computation of efficient static mappings requires an a priori knowledge of the
dynamic behavior of the target machine with respect to the programs which are
run on it. This knowledge is synthesized in a cost function, the nature of which
determines the characteristics of the desired optimal mappings. The goal of our
mapping algorithm is to minimize some communication cost function, while keeping
the load balance within a specified tolerance. The communication cost function fC
that we have chosen is the sum, for all edges, of their dilation multiplied by their
weight:
X
def
wS (eS ) |ρS,T (eS )| .
fC (τS,T , ρS,T ) =
eS ∈E(S)
This function, which has already been considered by several authors for hypercube target topologies [11, 21, 25], has several interesting properties: it is easy
to compute, allows incremental updates performed by iterative algorithms, and its
minimization favors the mapping of intensively intercommunicating processes onto
nearby processors; regardless of the type of routage implemented on the target
machine (store-and-forward or cut-through), it models the traffic on the interconnection network and thus the risk of congestion.
The strong positive correlation between values of this function and effective
execution times has been experimentally verified by Hammond [21] on the CM-2,
and by Hendrickson and Leland [26] on the nCUBE 2.
The quality of mappings is evaluated with respect to the criteria for quality that
we have chosen: the balance of the computation load across processors, and the
minimization of the interprocessor communication cost modeled by function fC .
These criteria lead to the definition of several parameters, which are described
below.
For load balance, one can define µmap , the average load per computational
power unit (which does not depend on the mapping), and δmap , the load imbalance
8
ratio, as
def
µmap =
P
wS (vS )
P
wT (vT )
vS ∈V (S)
and
vT ∈V (T )
def
δmap =

P  1
wT (vT )
vT ∈V (T ) P
vS ∈ V (S)
τS,T (vS ) = vT
P

wS (vS ) − µmap 
wS (vS )
.
vS ∈V (S)
However, since the maximum load imbalance ratio is provided by the user in input
of the mapping, the information given by these parameters is of little interest, since
what matters is the minimization of the communication cost function under this
load balance constraint.
For communication, the straightforward parameter to consider is fC . It can be
normalized as µexp , the average edge expansion, which can be compared to µdil ,
the average edge dilation; these are defined as
P
|ρS,T (eS )|
fC
def
def eS ∈E(S)
P
µexp =
and
µdil =
.
wS (eS )
|E(S)|
eS ∈E(S)
def µ
is smaller than 1 when the mapper succeeds in putting heavily interδexp = µexp
dil
communicating processes closer to each other than it does for lightly communicating
processes; they are equal if all edges have same weight.
3.1.3
The Dual Recursive Bipartitioning algorithm
Our mapping algorithm uses a divide and conquer approach to recursively allocate
subsets of processes to subsets of processors [43]. It starts by considering a set of
processors, also called domain, containing all the processors of the target machine,
and with which is associated the set of all the processes to map. At each step, the
algorithm bipartitions a yet unprocessed domain into two disjoint subdomains, and
calls a graph bipartitioning algorithm to split the subset of processes associated with
the domain across the two subdomains, as sketched in the following.
mapping (D, P)
Set_Of_Processors D;
Set_Of_Processes
P;
{
Set_Of_Processors D0, D1;
Set_Of_Processes
P0, P1;
if (|P| == 0) return;
if (|D| == 1) {
result (D, P);
return;
}
/* If nothing to do.
*/
/* If one processor in D */
/* P is mapped onto it. */
(D0, D1) = processor_bipartition (D);
(P0, P1) = process_bipartition
(P, D0, D1);
mapping (D0, P0);
/* Perform recursion. */
mapping (D1, P1);
}
The association of a subdomain with every process defines a partial mapping of the
process graph. As bipartitionings are performed, the subdomain sizes decrease, up
9
to give a complete mapping when all subdomains are of size one.
The above algorithm lies on the ability to define five main objects:
• a domain structure, which represents a set of processors in the target architecture;
• a domain bipartitioning function, which, given a domain, bipartitions it in two
disjoint subdomains;
• a domain distance function, which gives, in the target graph, a measure of the
distance between two disjoint domains. Since domains may not be convex nor
connected, this distance may be estimated. However, it must respect certain
homogeneity properties, such as giving more accurate results as domain sizes
decrease. The domain distance function is used by the graph bipartitioning
algorithms to compute the communication function to minimize, since it allows
the mapper to estimate the dilation of the edges that link vertices which belong
to different domains. Using such a distance function amounts to considering
that all routings will use shortest paths on the target architecture, which
is how most parallel machines actually do. We have thus chosen that our
program would not provide routings for the communication channels, leaving
their handling to the communication system of the target machine;
• a process subgraph structure, which represents the subgraph induced by a
subset of the vertex set of the original source graph;
• a process subgraph bipartitioning function, which bipartitions subgraphs in
two disjoint pieces to be mapped onto the two subdomains computed by the
domain bipartitioning function.
All these routines are seen as black boxes by the mapping program, which can thus
accept any kind of target architecture and process bipartitioning functions.
3.1.4
Partial cost function
The production of efficient complete mappings requires that all graph bipartitionings favor the criteria that we have chosen. Therefore, the bipartitioning of a
subgraph S ′ of S should maintain load balance within the user-specified tolerance,
and minimize the partial communication cost function fC′ , defined as
X
def
wS ({v, v ′ }) |ρS,T ({v, v ′ })| ,
fC′ (τS,T , ρS,T ) =
v ∈ V (S ′ )
{v, v ′ } ∈ E(S)
which accounts for the dilation of edges internal to subgraph S ′ as well as for the
one of edges which belong to the cocycle of S ′ , as shown in Figure 1. Taking into
account the partial mapping results issued by previous bipartitionings makes it possible to avoid local choices that might prove globally bad, as explained below. This
amounts to incorporating additional constraints to the standard graph bipartitioning problem, turning it into a more general optimization problem termed skewed
graph partitioning by some authors [27].
10
D
D
D0
D0
D1
a. Initial position.
D1
b. After one vertex is moved.
Figure 1: Edges accounted for in the partial communication cost function when
bipartitioning the subgraph associated with domain D between the two subdomains
D0 and D1 of D. Dotted edges are of dilation zero, their two ends being mapped
onto the same subdomain. Thin edges are cocycle edges.
3.1.5
Execution scheme
From an algorithmic point of view, our mapper behaves as a greedy algorithm, since
the mapping of a process to a subdomain is never reconsidered, and at each step
of which iterative algorithms can be applied. The double recursive call performed
at each step induces a recursion scheme in the shape of a binary tree, each vertex
of which corresponds to a bipartitioning job, that is, the bipartitioning of both a
domain and its associated subgraph.
In the case of depth-first sequencing, as written in the above sketch, bipartitioning jobs run in the left branches of the tree have no information on the distance between the vertices they handle and neighbor vertices to be processed in
the right branches. On the contrary, sequencing the jobs according to a by-level
(breadth-first) travel of the tree allows any bipartitioning job of a given level to
have information on the subdomains to which all the processes have been assigned
at the previous level. Thus, when deciding in which subdomain to put a given process, a bipartitioning job can account for the communication costs induced by its
neighbor processes, whether they are handled by the job itself or not, since it can
estimate in fC′ the dilation of the corresponding edges. This results in an interesting
feedback effect: once an edge has been kept in a cut between two subdomains, the
distance between its end vertices will be accounted for in the partial communication
cost function to be minimized, and following jobs will be more likely to keep these
vertices close to each other, as illustrated in Figure 2. The relative efficiency of
depth-first and breadth-first sequencing schemes with respect to the structure of
the source and target graphs is discussed in [46].
3.1.6
Graph bipartitioning methods
The core of our recursive mapping algorithm uses process graph bipartitioning methods as black boxes. It allows the mapper to run any type of graph bipartitioning
method compatible with our criteria for quality. Bipartitioning jobs maintain an internal image of the current bipartition, indicating for every vertex of the job whether
it is currently assigned to the first or to the second subdomain. It is therefore possible to apply several different methods in sequence, each one starting from the result
of the previous one, and to select the methods with respect to the job characteristics, thus enabling us to define mapping strategies. The currently implemented
11
CL0
CL0
CL1
CL1
D
D
CL2
CL2
CL1
CL2
a. Depth-first sequencing.
b. Breadth-first sequencing.
Figure 2: Influence of depth-first and breadth-first sequencings on the bipartitioning
of a domain D belonging to the leftmost branch of the bipartitioning tree. With
breadth-first sequencing, the partial mapping data regarding vertices belonging to
the right branches of the bipartitioning tree are more accurate (C.L. stands for “Cut
Level”).
graph bipartitioning methods are listed below.
Band
Like the multi-level method which will be described below, the band method
is a meta-algorithm, in the sense that it does not itself compute partitions, but
rather helps other partitioning algorithms perform better. It is a refinement
algorithm which, from a given initial partition, extracts a band graph of given
width (which only contains graph vertices that are at most at this distance
from the separator), calls a partitioning strategy on this band graph, and
projects back the refined partition on the original graph. This method was
designed to be able to use expensive partitioning heuristics, such as genetic
algorithms, on large graphs, as it dramatically reduces the problem space by
several orders of magnitude. However, it was found that, in a multi-level
context, it also improves partition quality, by coercing partitions in a problem
space that derives from the one which was globally defined at the coarsest
level, thus preventing local optimization refinement algorithms to be trapped
in local optima of the finer graphs [8].
Diffusion
This global optimization method, presented in [44], flows two kinds of antagonistic liquids, scotch and anti-scotch, from two source vertices, and sets the
new frontier as the limit between vertices which contain scotch and the ones
which contain anti-scotch. In order to add load-balancing constraints to the
algorithm, a constant amount of liquid disappears from every vertex per unit
of time, so that no domain can spread across more than half of the vertices.
Because selecting the source vertices is essential to the obtainment of useful results, this method has been hard-coded so that the two source vertices
are the two vertices of highest indices, since in the band method these are
the anchor vertices which represent all of the removed vertices of each part.
Therefore, this method must be used on band graphs only, or on specifically
crafted graphs.
Exactifier
This greedy algorithm refines the current partition so as to reduce load imbal12
ance as much as possible, while keeping the value of the communication cost
function as small as possible. The vertex set is scanned in order of decreasing
vertex weights, and vertices are moved from one subdomain to the other if
doing so reduces load imbalance. When several vertices have same weight,
the vertex whose swap decreases most the communication cost function is selected first. This method is used in post-processing of other methods when
load balance is mandatory. For weighted graphs, the strict enforcement of
load balance may cause the swapping of isolated vertices of small weight, thus
greatly increasing the cut. Therefore, great care should be taken when using
this method if connectivity or cut minimization are mandatory.
Fiduccia-Mattheyses
The Fiduccia-Mattheyses heuristics [12] is an almost-linear improvement of
the famous Kernighan-Lin algorithm [35]. It tries to improve the bipartition
that is input to it by incrementally moving vertices between the subsets of
the partition, as long as it can find sequences of moves that lower its communication cost. By considering sequences of moves instead of single swaps, the
algorithm allows hill-climbing from local minima of the cost function. As an
extension to the original Fiduccia-Mattheyses algorithm, we have developed
new data structures, based on logarithmic indexings of arrays, that allow us
to handle weighted graphs while preserving the almost-linearity in time of the
algorithm [46].
As several authors quoted before [24, 32], the Fiduccia-Mattheyses algorithm
gives better results when trying to optimize a good starting partition. Therefore, it should not be used on its own, but rather after greedy starting methods
such as the Gibbs-Poole-Stockmeyer or the greedy graph growing methods.
Gibbs-Poole-Stockmeyer
This greedy bipartitioning method derives from an algorithm proposed by
Gibbs, Poole, and Stockmeyer to minimize the dilation of graph orderings,
that is, the maximum absolute value of the difference between the numbers of
neighbor vertices [18]. The graph is sliced by using a breadth-first spanning
tree rooted at a randomly chosen vertex, and this process is iterated by selecting a new root vertex within the last layer as long as the number of layers
increases. Then, starting from the current root vertex, vertices are assigned
layer after layer to the first subdomain, until half of the total weight has been
processed. Remaining vertices are then allocated to the second subdomain.
As for the original Gibbs, Poole, and Stockmeyer algorithm, it is assumed that
the maximization of the number of layers results in the minimization of the
sizes –and therefore of the cocycles– of the layers. This property has already
been used by George and Liu to reorder sparse linear systems using the nested
dissection method [17], and by Simon in [56].
Greedy graph growing
This greedy algorithm, which has been proposed by Karypis and Kumar [31],
belongs to the GRASP (“Greedy Randomized Adaptive Search Procedure”)
class [36]. It consists in selecting an initial vertex at random, and repeatedly
adding vertices to this growing subset, such that each added vertex results
in the smallest increase in the communication cost function. This process,
which stops when load balance is achieved, is repeated several times in order
to explore (mostly in a gradient-like fashion) different areas of the solution
space, and the best partition found is kept.
13
Multi-level
This algorithm, which has been studied by several authors [4, 23, 31] and
should be considered as a strategy rather than as a method since it uses other
methods as parameters, repeatedly reduces the size of the graph to bipartition
by finding matchings that collapse vertices and edges, computes a partition
for the coarsest graph obtained, and projects the result back to the original
graph, as shown in Figure 3. The multi-level method, when used in conjuncRefined partition
Projected partition
Coarsening
phase
Uncoarsening
phase
Initial partitioning
Figure 3: The multi-level partitioning process. In the uncoarsening phase, the light
and bold lines represent for each level the projected partition obtained from the
coarser graph, and the partition obtained after refinement, respectively.
tion with the Fiduccia-Mattheyses method to compute the initial partitions
and refine the projected partitions at every level, usually leads to a significant improvement in quality with respect to the plain Fiduccia-Mattheyses
method. By coarsening the graph used by the Fiduccia-Mattheyses method
to compute and project back the initial partition, the multi-level algorithm
broadens the scope of the Fiduccia-Mattheyses algorithm, and makes possible
for it to account for topological structures of the graph that would else be of
a too high level for it to encompass in its local optimization process.
3.1.7
Mapping onto variable-sized architectures
Several constrained graph partitioning problems can be modeled as mapping the
problem graph onto a target architecture, the number of vertices and topology of
which depend dynamically on the structure of the subgraphs to bipartition at each
step.
Variable-sized architectures are supported by the DRB algorithm in the following way: at the end of each bipartitioning step, if any of the variable subdomains
is empty (that is, all vertices of the subgraph are mapped only to one of the subdomains), then the DRB process stops for both subdomains, and all of the vertices
are assigned to their parent subdomain; else, if a variable subdomain has only one
vertex mapped onto it, the DRB process stops for this subdomain, and the vertex
is assigned to it.
The moment when to stop the DRB process for a specific subgraph can be controlled by defining a bipartitioning strategy that tests for the validity of a criterion
at each bipartitioning step, and maps all of the subgraph vertices to one of the
subdomains when it becomes false.
14
3.2
Sparse matrix ordering by hybrid incomplete nested dissection
When solving large sparse linear systems of the form Ax = b, it is common to
precede the numerical factorization by a symmetric reordering. This reordering is
chosen in such a way that pivoting down the diagonal in order on the resulting
permuted matrix P AP T produces much less fill-in and work than computing the
factors of A by pivoting down the diagonal in the original order (the fill-in is the
set of zero entries in A that become non-zero in the factored matrix).
3.2.1
Minimum Degree
The minimum degree algorithm [57] is a local heuristic that performs its pivot
selection by iteratively selecting from the graph a node of minimum degree.
The minimum degree algorithm is known to be a very fast and general purpose
algorithm, and has received much attention over the last three decades (see for
example [1, 16, 41]). However, the algorithm is intrinsically sequential, and very
little can be theoretically proved about its efficiency.
3.2.2
Nested dissection
The nested dissection algorithm [17] is a global, heuristic, recursive algorithm which
computes a vertex set S that separates the graph into two parts A and B, ordering
S with the highest remaining indices. It then proceeds recursively on parts A and B
until their sizes become smaller than some threshold value. This ordering guarantees
that, at each step, no non zero term can appear in the factorization process between
unknowns of A and unknowns of B.
Many theoretical results have been carried out on nested dissection ordering [7, 40], and its divide and conquer nature makes it easily parallelizable. The
main issue of the nested dissection ordering algorithm is thus to find small vertex
separators that balance the remaining subgraphs as evenly as possible. Most often,
vertex separators are computed by using direct heuristics [28, 38], or from edge
separators [50, and included references] by minimum cover techniques [9, 30], but
other techniques such as spectral vertex partitioning have also been used [51].
Provided that good vertex separators are found, the nested dissection algorithm
produces orderings which, both in terms of fill-in and operation count, compare
favorably [20, 31, 48] to the ones obtained with the minimum degree algorithm [41].
Moreover, the elimination trees induced by nested dissection are broader, shorter,
and better balanced, and therefore exhibit much more concurrency in the context
of parallel Cholesky factorization [3, 14, 15, 20, 48, 55, and included references].
3.2.3
Hybridization
Due to their complementary nature, several schemes have been proposed to
hybridize the two methods [28, 34, 48]. However, to our knowledge, only loose
couplings have been achieved: incomplete nested dissection is performed on the
graph to order, and the resulting subgraphs are passed to some minimum degree
algorithm. This results in the fact that the minimum degree algorithm does not
have exact degree values for all of the boundary vertices of the subgraphs, leading
to a misbehavior of the vertex selection process.
15
Our ordering program implements a tight coupling of the nested dissection and
minimum degree algorithms, that allows each of them to take advantage of the information computed by the other. First, the nested dissection algorithm provides exact
degree values for the boundary vertices of the subgraphs passed to the minimum
degree algorithm (called halo minimum degree since it has a partial visibility of the
neighborhood of the subgraph). Second, the minimum degree algorithm returns the
assembly tree that it computes for each subgraph, thus allowing for supervariable
amalgamation, in order to obtain column-blocks of a size suitable for BLAS3 block
computations.
As for our mapping program, it is possible to combine ordering methods into
ordering strategies, which allow the user to select the proper methods with respect
to the characteristics of the subgraphs.
The ordering program is completely parametrized by its ordering strategy. The
nested dissection method allows the user to take advantage of all of the graph
partitioning routines that have been developed in the earlier stages of the Scotch
project. Internal ordering strategies for the separators are relevant in the case of
sequential or parallel [19, 52, 53, 54] block solving, to select ordering algorithms
that minimize the number of extra-diagonal blocks [7], thus allowing for efficient
use of BLAS3 primitives, and to reduce inter-processor communication.
3.2.4
Performance criteria
The quality of orderings is evaluated with respect to several criteria. The first
one, NNZ, is the number of non-zero terms in the factored reordered matrix. The
second one, OPC, is the operation count, that is the number of arithmetic operations
required to factor the matrix. The operation count that we have considered takes
into consideration all operations (additions, subtractions, multiplications, divisions)
P
required by Cholesky factorization, except square roots; it is equal to c n2c , where
nc is the number of non-zeros of column c of the factored matrix, diagonal included.
A third criterion for quality is the shape of the elimination tree; concurrency in
parallel solving is all the higher as the elimination tree is broad and short. To
measure its quality, several parameters can be defined: hmin , hmax , and havg denote
the minimum, maximum, and average heights of the tree1 , respectively, and hdlt
is the variance, expressed as a percentage of havg . Since small separators result in
small chains in the elimination tree, havg should also indirectly reflect the quality
of separators.
3.2.5
Ordering methods
The core of our ordering algorithm uses graph ordering methods as black boxes,
which allows the orderer to run any type of ordering method. In addition to yielding
orderings of the subgraphs that are passed to them, these methods may compute
column block partitions of the subgraphs, that are recorded in a separate tree
structure. The currently implemented graph ordering methods are listed below.
Halo approximate minimum degree
The halo approximate minimum degree method [49] is an improvement of
the approximate minimum degree [1] algorithm, suited for use on subgraphs
1 We do not consider as leaves the disconnected vertices that are present in some meshes, since
they do not participate in the solving process.
16
produced by nested dissection methods. Its interest compared to classical minimum degree algorithms is that boundary vertices are processed using their
real degree in the global graph rather than their (much smaller) degree in the
subgraph, resulting in smaller fill-in and operation count. This method also
implements amalgamation techniques that result in efficient block computations in the factoring and the solving processes.
Halo approximate minimum fill
The halo approximate minimum fill method is a variant of the halo approximate minimum degree algorithm, where the criterion to select the next vertex
to permute is not based on its current estimated degree but on the minimization of the induced fill.
Graph compression
The graph compression method [2] merges cliques of vertices into single nodes,
so as to speed-up the ordering of the compressed graph. It also results in some
improvement of the quality of separators, especially for stiffness matrices.
Gibbs-Poole-Stockmeyer
This method is mainly used on separators to reduce the number and extent
of extra-diagonal blocks.
Simple method
Vertices are ordered consecutively, in the same order as they are stored in the
graph. This is the fastest method to use on separators when the shape of
extra-diagonal structures is not a concern.
Nested dissection
Incomplete nested dissection method. Separators are computed recursively on
subgraphs, and specific ordering methods are applied to the separators and
to the resulting subgraphs (see sections 3.2.2 and 3.2.3).
3.2.6
Graph separation methods
The core of our incomplete nested dissection algorithm uses graph separation
methods as black boxes. It allows the orderer to run any type of graph separation
method compatible with our criteria for quality, that is, reducing the size of the
vertex separator while maintaining the loads of the separated parts within some
user-specified tolerance. Separation jobs maintain an internal image of the current
vertex separator, indicating for every vertex of the job whether it is currently
assigned to one of the two parts, or to the separator. It is therefore possible to
apply several different methods in sequence, each one starting from the result of
the previous one, and to select the methods with respect to the job characteristics,
thus enabling the definition of separation strategies.
The currently implemented graph separation methods are listed below.
Fiduccia-Mattheyses
This is a vertex-oriented version of the original, edge-oriented, FiducciaMattheyses heuristics described in page 13.
Greedy graph growing
This is a vertex-oriented version of the edge-oriented greedy graph growing
algorithm described in page 13.
17
Multi-level
This is a vertex-oriented version of the edge-oriented multi-level algorithm
described in page 14.
Thinner
This greedy algorithm refines the current separator by removing all of the
exceeding vertices, that is, vertices that do not have neighbors in both parts.
It is provided as a simple gradient refinement algorithm for the multi-level
method, and is clearly outperformed by the Fiduccia-Mattheyses algorithm.
Vertex cover
This algorithm computes a vertex separator by first computing an edge separator, that is, a bipartition of the graph, and then turning it into a vertex separator by using the method proposed by Pothen and Fang [50]. This method
requires the computation of maximal matchings in the bipartite graphs associated with the edge cuts, which are built using Duff’s variant [9] of the
Hopcroft and Karp algorithm [30]. Edge separators are computed by using a
bipartitioning strategy, which can use any of the graph bipartitioning methods
described in section 3.1.6, page 11.
4
4.1
Updates
Changes from version 4.0
Scotch has gone parallel with the release of PT-Scotch, the Parallel Threaded
Scotch. People interested in these parallel routines should refer to the PT-Scotch
and libScotch 5.1 User’s Guide [45], which extends this manual.
A compatibility library has been developed to allow users to try and use Scotch
in programs that were designed to use MeTiS. Please refer to Section 7.14 for more
information.
Scotch can now handle compressed streams on the fly, in several widely used
formats such as gzip, bzip2 or lzma. Please refer to Section 6.2 for more information.
5
Files and data structures
For the sake of portability, readability, and reduction of storage space, all the data
files shared by the different programs of the Scotch project are coded in plain
ASCII text exclusively. Although we may speak of “lines” when describing file formats, text-formatting characters such as newlines or tabulations are not mandatory,
and are not taken into account when files are read. They are only used to provide
better readability and understanding. Whenever numbers are used to label objects,
and unless explicitely stated, numberings always start from zero, not one.
5.1
Graph files
Graph files, which usually end in “.grf” or “.src”, describe valuated graphs, which
can be valuated process graphs to be mapped onto target architectures, or graphs
representing the adjacency structures of matrices to order.
Graphs are represented by means of adjacency lists: the definition of each
vertex is accompanied by the list of all of its neighbors, i.e. all of its adjacent arcs.
18
Therefore, the overall number of edge data is twice the number of edges.
Since version 3.3 has been introduced a new file format, referred to as the “newstyle” file format, which replaces the previous, “old-style”, file format. The two
advantages of the new-style format over its predecessor are its greater compacity,
which results in shorter I/O times, and its ability to handle easily graphs output
by C or by Fortran programs.
Starting from version 4.0, only the new format is supported. To convert
remaining old-style graph files into new-style graph files, one should get version 3.4
of the Scotch distribution, which comprises the scv file converter, and use it to
produce new-style Scotch graph files from the old-style Scotch graph files which
it is able to read. See section 6.3.5 for a description of gcv, formerly called scv.
The first line of a graph file holds the graph file version number, which is currently 0. The second line holds the number of vertices of the graph (referred to as
vertnbr in libScotch; see for instance Figure 16, page 49, for a detailed example),
followed by its number of arcs (unappropriately called edgenbr, as it is in fact equal
to twice the actual number of edges). The third line holds two figures: the graph
base index value (baseval), and a numeric flag.
The graph base index value records the value of the starting index used to
describe the graph; it is usually 0 when the graph has been output by C programs,
and 1 for Fortran programs. Its purpose is to ease the manipulation of graphs within
each of these two environments, while providing compatibility between them.
The numeric flag, similar to the one used by the Chaco graph format [24], is
made of three decimal digits. A non-zero value in the units indicates that vertex
weights are provided. A non-zero value in the tenths indicates that edge weights
are provided. A non-zero value in the hundredths indicates that vertex labels are
provided; if it is the case, vertices can be stored in any order in the file; else, natural
order is assumed, starting from the graph base index.
This header data is then followed by as many lines as there are vertices in the
graph, that is, vertnbr lines. Each of these lines begins with the vertex label,
if necessary, the vertex load, if necessary, and the vertex degree, followed by the
description of the arcs. An arc is defined by the load of the edge, if necessary, and
by the label of its other end vertex. The arcs of a given vertex can be provided
in any order in its neighbor list. If vertex labels are provided, vertices can also be
stored in any order in the file.
Figure 4 shows the contents of a graph file modeling a cube with unity vertex
and edge weights and base 0.
0
8
0
3
3
3
3
3
3
3
3
24
000
4
5
6
7
0
1
2
3
2
3
0
1
6
7
4
5
1
0
3
2
5
4
7
6
Figure 4: Graph file representing a cube.
19
5.2
Mesh files
Mesh files, which usually end in “.msh”, describe valuated meshes, made of elements
and nodes, the elements of which can be mapped onto target architectures, and the
nodes of which can be reordered.
Meshes are bipartite graphs, in the sense that every element is connected to the
nodes that it comprises, and every node is connected to the elements to which it
belongs. No edge connects any two element vertices, nor any two node vertices.
One can also think of meshes as hypergraphs, such that nodes are the vertices
of the hypergraph and elements are hyper-edges which connect multiple nodes, or
reciprocally such that elements are the vertices of the hypergraph and nodes are
hyper-edges which connect multiple elements.
Since meshes are graphs, the structure of mesh files resembles very much the
one of graph files described above in section 5.1, and differs only by its header,
which indicates which of the vertices are node vertices and element vertices.
The first line of a mesh file holds the mesh file version number, which is currently
1. Graph and mesh version numbers will always differ, which enables application
programs to accept both file formats and adapt their behavior according to the
type of input data. The second line holds the number of elements of the mesh
(velmnbr), followed by its number of nodes (vnodnbr), and by its overall number of
arcs (edgenbr, that is, twice the number of edges which connect elements to nodes
and vice-versa).
The third line holds three figures: the base index of the first element vertex in
memory (velmbas), the base index of the first node vertex in memory (vnodbas),
and a numeric flag.
The Scotch mesh file format requires that all nodes and all elements be assigned
to contiguous ranges of indices. Therefore, either all element vertices are defined
before all node vertices, or all node vertices are defined before all element vertices.
The node and element base indices indicate at the same time whether elements or
nodes are put in the first place, as well as the value of the starting index used to
describe the graph. Indeed, if velmbas < vnodbas, then elements have the smallest
indices, velmbas is the base value of the underlying graph (that is, baseval =
velmbas), and velmbas + velmnbr = vnodbas holds. Conversely, if velmbas >
vnodbas, then nodes have the smallest indices, vnodbas is the base value of the
underlying graph, (that is, baseval = vnodbas), and vnodbas+vnodnbr = velmbas
holds.
The numeric flag, similar to the one used by the Chaco graph format [24], is
made of three decimal digits. A non-zero value in the units indicates that vertex
weights are provided. A non-zero value in the tenths indicates that edge weights
are provided. A non-zero value in the hundredths indicates that vertex labels are
provided; if it is the case, and if velmbas < vnodbas (resp. velmbas > vnodbas),
the velmnbr (resp. vnodnbr) first vertex lines are assumed to be element (resp.
node) vertices, irrespective of their vertex labels, and the vnodnbr (resp. velmnbr)
remaining vertex lines are assumed to be node (resp. element) vertices; else, natural
order is assumed, starting at the underlying graph base index (baseval).
This header data is then followed by as many lines as there are node and element
vertices in the graph. These lines are similar to the ones of the graph format, except
that, in order to save disk space, the numberings of nodes and elements all start
from the same base value, that is, min(velmbas, vnodbas) (also called baseval, like
for regular graphs).
20
For example, Figure 5 shows the contents of the mesh file modeling three square
elements, with unity vertex and edge weights, elements defined before nodes, and
numbering of the underlying graph starting from 1. In memory, the three elements
are labeled from 1 to 3, and the eight nodes are labeled from 4 to 11. In the file,
the three elements are still labeled from 1 to 3, while the eight nodes are labeled
from 1 to 8.
When labels are used, elements and nodes may have similar labels, but not two
elements, nor two nodes, should have the same labels.
4
10
2
5
11
1
6
7
3
8
9
1
3
1
4
4
4
1
2
2
2
1
1
1
2
8
4
2
7
5
2
2
1
1
3
3
2
2
(= 5)
(= 10)
(= 8)
24
000
8 (= 11)
2 (= 5)
6 (= 9)
4
8
3
(= 7)
(= 11)
(= 6)
3
1
4
(= 6)
(= 4)
(= 7)
1
3
3
1
Figure 5: Mesh file representing three square elements, with unity vertex and edge
weights. Elements are defined before nodes, and numbering of the underlying graph
starts from 1. The left part of the figure shows the mesh representation in memory,
with consecutive element and node indices. The right part of the figure shows
the contents of the file, with both element and node numberings starting from 1,
the minimum of the element and node base values. Corresponding node indices in
memory are shown in parentheses for the sake of comprehension.
5.3
Geometry files
Geometry files, which usually end in “.xyz”, hold the coordinates of the vertices
of their associated graph or mesh. These files are not used in the mapping process
itself, since only topological properties are taken into account then (mappings are
computed regardless of graph geometry). They are used by visualization programs
to compute graphical representations of mapping results.
The first string to appear in a geometry file codes for its type, or dimensionality. It is “1” if the file contains unidimensional coordinates, “2” for bidimensional
coordinates, and “3” for tridimensional coordinates. It is followed by the number of
coordinate data stored in the file, which should be at least equal to the number of
vertices of the associated graph or mesh, and by that many coordinate lines. Each
coordinate line holds the label of the vertex, plus one, two or three real numbers
which are the (X), (X,Y), or (X,Y,Z), coordinates of the graph vertices, according
to the graph dimensionality.
Vertices can be stored in any order in the file. Moreover, a geometry file can have
more coordinate data than there are vertices in the associated graph or mesh file;
only coordinates the labels of which match labels of graph or mesh vertices will be
21
taken into account. This feature allows all subgraphs of a given graph or mesh to
share the same geometry file, provided that graph vertex labels remain unchanged.
For example, Figure 6 shows the contents of the 3D geometry file associated with
the graph of Figure 4.
3
8
0
1
2
3
4
5
6
7
0.0
0.0
0.0
0.0
1.0
1.0
1.0
1.0
0.0
0.0
1.0
1.0
0.0
0.0
1.0
1.0
0.0
1.0
0.0
1.0
0.0
1.0
0.0
1.0
Figure 6: Geometry file associated with the graph file of Figure 4.
5.4
Target files
Target files describe the architectures onto which source graphs are mapped. Instead
of containing the structure of the target graph itself, as source graph files do, target
files define how target graphs are bipartitioned and give the distances between all
pairs of vertices (that is, processors). Keeping the bipartitioning information within
target files avoids recomputing it every time a target architecture is used. We are
allowed to do so because, in our approach, the recursive bipartitioning of the target
graph is fully independent with respect to that of the source graph (however, the
opposite is false).
For space and time saving issues, some classical homogeneous architectures (2D
and 3D meshes and tori, hypercubes, complete graphs, etc.) have been algorithmically coded within the mapper itself by the means of built-in functions. Instead of
containing the whole graph decomposition data, their target files hold only a few
values, used as parameters by the built-in functions.
5.4.1
Decomposition-defined architecture files
Decomposition-defined architecture files are the standard way to describe weighted
and/or irregular target architectures. Several file formats exist, but we only present
here the most humanly readable one, which begins in “deco 0” (“deco” stands for
“decomposition-defined” architecture, and “0” is the format type).
The “deco 0” header is followed by two integer numbers, which are the number
of processors and the largest terminal number used in the decomposition, respectively. Two arrays follow. The first array has as many lines as there are processors.
Each of these lines holds three numbers: the processor label, the processor weight
(that is an estimation of its computational power), and its terminal number. The
terminal number associated with every processor is obtained by giving the initial
domain holding all the processors number 1, and by numbering the two subdomains
of a given domain of number i with numbers 2i and 2i + 1. The second array is
a lower triangular diagonal-less matrix that gives the distance between all pairs of
processors. This distance matrix, combined with the decomposition tree coded by
terminal numbers, allows the evaluation by averaging of the distance between all
pairs of domains. In order for the mapper to behave properly, distances between
22
processors must be strictly positive numbers. Therefore, null distances are not accepted. For instance, Figure 7 shows the contents of the architecture decomposition
file for UB(2, 3), the binary de Bruijn graph of dimension 3, as computed by the
amk grf program.
1
3
2
7
6
15 14
12 13
4
9 11
5
8 10
deco 0
8 15
0 1 15
1 1 14
2 1 13
3 1 11
4 1 12
5 1 9
6 1 8
7 1 10
1
2 1
2 1 2
1 1 1 2
3 2 1 1 2
2 2 2 1 1 1
3 2 3 1 2 2 1
Figure 7: Target decomposition file for UB(2, 3). The terminal numbers associated
with every processor define a unique recursive bipartitioning of the target graph.
5.4.2
Algorithmically-coded architecture files
All algorithmically-coded architectures are defined with unity edge and vertex
weights. They start with an abbreviation name of the architecture, followed by
parameters specific to the architecture. The available built-in architecture definitions are listed below.
cmplt size
Defines a complete graph with size vertices. The vertex labels are numbers
between 0 and size − 1.
cmpltw size load0 load1 . . . loadsize−1
Defines a weighted complete graph with size vertices. The vertex labels are
numbers between 0 and size − 1, and vertices are assigned integer weights in
the order in which these are provided.
hcub dim
Defines a binary hypercube of dimension dim. The vertex labels are the
decimal values of the binary representations of the vertex coordinates in the
hypercube.
leaf height cluster weight
Defines a tree-leaf architecture with height levels and 2height vertices. The
tree-leaf graph models a machine the topology of which is a complete binary
tree, such that leaves are processors and all other nodes are communication
routers, as shown in Figure 8. Only the leaves are used to map processes, but
distances between them are computed by considering the whole tree. This
graph is used to represent multi-stage machines with constant bandwidth,
23
Figure 8: The “tree-leaf” graph of height 3. Processors are drawn in black and
routers in grey.
such as the CM-5 [37] for which experiments have shown that bandwidth is
constant between every pair of processors and hardly depends on network
congestion [39], or the SP-2 with power-of-two number of nodes.
The two additional parameters cluster and weight serve to model heterogeneous architectures for which multiprocessor nodes having several highly
interconnected processors (typically by means of shared memory) are linked
by means of networks of lower bandwidth. cluster represents the number
of levels to traverse, starting from the root of the leaf, before reaching the
multiprocessors, each multiprocessor having 2height−cluster nodes. weight is
the relative cost of extra-cluster links, that is, links in the upper levels of the
tree-leaf graph. Links within clusters are assumed to have weight 1.
When there are no clusters at all, that is, in the case of purely homogeneous
architectures, set cluster to be equal to height, and weight to 1.
mesh2D dimX dimY
Defines a bidimensional array of dimX columns by dimY rows. The vertex
with coordinates (posX, posY) has label posY × dimX + posX.
mesh3D dimX dimY dimZ
Defines a tridimensional array of dimX columns by dimY rows by dimZ levels. The vertex with coordinates (posX,posY,posZ ) has label (posZ × dimY +
posY) × dimX + posX.
torus2D dimX dimY
Defines a bidimensional array of dimX columns by dimY rows, with
wraparound edges. The vertex with coordinates (posX, posY) has label
posY × dimX + posX.
torus3D dimX dimY dimZ
Defines a tridimensional array of dimX columns by dimY rows by dimZ levels,
with wraparound edges. The vertex with coordinates (posX,posY,posZ ) has
label (posZ × dimY + posY) × dimX + posX.
5.4.3
Variable-sized architecture files
Variable-sized architectures are a class of algorithmically-coded architectures the
size of which is not defined a priori. As for fixed-size algorithmically-coded architectures, they start with an abbreviation name of the architecture, followed by
parameters specific to the architecture. The available built-in variable-sized architecture definitions are listed below.
varcmplt
Defines a variable-sized complete graph. Domains are labeled such that the
first domain is labeled 1, and the two subdomains of any domain i are labeled
24
2i and 2i + 1. The distance between any two subdomains i and j is 0 if i = j
and 1 else.
varhcub
Defines a variable-sized hypercube. Domains are labeled such that the first
domain is labeled 1, and the two subdomains of any domain i are labeled 2i
and 2i + 1. The distance between any two domains is the Hamming distance
between the common bits of the two domains, plus half of the absolute difference between the levels of the two domains, this latter term modeling the
average distance on unknown bits. For instance, the distance between subdomain 9 = 1001B , of level 3 (since its leftmost 1 has been shifted left thrice),
and subdomain 53 = 110101B , of level 5 (since its leftmost 1 has been shifted
left five times), is 2: it is 1, which is the number of bits which differ between
1101B (that is, 53 = 110101B shifted rightwards twice) and 1001B , plus 1,
which is half of the absolute difference between 5 and 3.
5.5
Mapping files
Mapping files, which usually end in “.map”, contain the result of the mapping of
source graphs onto target architectures. They associate a vertex of the target graph
with every vertex of the source graph.
Mapping files begin with the number of mapping lines which they contain, followed by that many mapping lines. Each mapping line holds a mapping pair, made
of two integer numbers which are the label of a source graph vertex and the label
of the target graph vertex onto which it is mapped. Mapping pairs can be stored
in any order in the file; however, labels of source graph vertices must be all different. For example, Figure 9 shows the result obtained when mapping the source
graph of Figure 4 onto the target architecture of Figure 7. This one-to-one embedding of H(3) into UB(2, 3) has dilation 1, except for one hypercube edge which has
dilation 3.
8
0
1
2
3
4
5
6
7
1
3
2
5
0
7
4
6
Figure 9: Mapping file obtained when mapping the hypercube source graph of
Figure 4 onto the binary de Bruijn architecture of Figure 7.
Mapping files are also used on output of the block orderer to represent the
allocation of the vertices of the original graph to the column blocks associated with
the ordering. In this case, column blocks are labeled in ascending order, such that
the number of a block is always greater than the ones of its predecessors in the
elimination process, that is, its leaves in the elimination tree.
5.6
Ordering files
Ordering files, which usually end in “.ord”, contain the result of the ordering of
source graphs or meshes that represent sparse matrices. They associate a number
25
with every vertex of the source graph or mesh.
The structure of ordering files is analogous to the one of mapping files; they
differ only by the meaning of their data.
Ordering files begin with the number of ordering lines which they contain, that
is the number of vertices in the source graph or the number of nodes in the source
mesh, followed by that many ordering lines. Each ordering line holds an ordering
pair, made of two integer numbers which are the label of a source graph or mesh
vertex and its rank in the ordering. Ranks range from the base value of the graph or
mesh (baseval) to the base value plus the number of vertices (resp. nodes), minus
one (baseval + vertnbr − 1 for graphs, and baseval + vnodnbr − 1 for meshes).
Ordering pairs can be stored in any order in the file; however, indices of source
vertices must be all different.
For example, Figure 10 shows the result obtained when reordering the source
graph of Figure 4.
8
0
1
2
3
4
5
6
7
6
3
2
7
1
5
4
0
Figure 10: Ordering file obtained when reordering the hypercube graph of Figure 4.
The advantage of having both graph and mesh orderings start from baseval
(and not vnodbas in the case of meshes) is that an ordering computed on the nodal
graph of some mesh has the same structure as an ordering computed from the native
mesh structure, allowing for greater modularity. However, in memory, permutation
indices for meshes are numbered from vnodbas to vnodbas + vnodnbr − 1.
5.7
Vertex list files
Vertex lists are used by programs that select vertices from graphs.
Vertex lists are coded as lists of integer numbers. The first integer is the number
of vertices in the list and the other integers are the labels of the selected vertices,
given in any order. For example, Figure 11 shows the list made from three vertices
of labels 2, 45, and 7.
3
2
45
7
Figure 11: Example of vertex list with three vertices of labels 2, 45, and 7.
6
Programs
The programs of the Scotch project belong to five distinct classes.
• Graph handling programs, the names of which begin in “g”, that serve to
build and test source graphs.
26
• Mesh handling programs, the names of which begin in “m”, that serve to build
and test source meshes.
• Target architecture handling programs, the names of which begin in “a”,
that allow the user to build and test decomposition-defined target files, and
especially to turn a source graph file into a target file.
• The mapping and ordering programs themselves.
• Output handling programs, which are the mapping performance analyzer, the
graph factorization program, and the graph, matrix, and mapping visualization program.
The general architecture of the Scotch project is displayed in Figure 12.
6.1
Invocation
The programs comprising the Scotch project have been designed to run in
command-line mode without any interactive prompting, so that they can be called
easily from other programs by means of “system ()” or “popen ()” system calls,
or be piped together on a single shell command line. In order to facilitate this,
whenever a stream name is asked for (either on input or output), the user may
put a single “-” to indicate standard input or output. Moreover, programs read
their input in the same order as stream names are given in the command line. It
allows them to read all their data from a single stream (usually the standard input),
provided that these data are ordered properly.
A brief on-line help is provided with all the programs. To get this help, use the
“-h” option after the program name. The case of option letters is not significant,
except when both the lower and upper cases of a letter have different meanings.
When passing parameters to the programs, only the order of file names is significant;
options can be put anywhere in the command line, in any order. Examples of use
of the different programs of the Scotch project are provided in section 9.
Error messages are standardized, but may not be fully explanatory. However,
most of the errors you may run into should be related to file formats, and located
in “...Load” routines. In this case, compare your data formats with the definitions
given in section 5, and use the gtst and mtst programs to check the consistency of
source graphs and meshes.
6.2
Using compressed files
Starting from version 5.0.6, Scotch allows users to provide and retrieve data in
compressed form. Since this feature requires that the compression and decompression tasks run in the same time as data is read or written, it can only be done
on systems which support multi-threading (Posix threads) or multi-processing (by
means of fork system calls).
To determine if a stream has to be handled in compressed form, Scotch checks
its extension. If it is “.gz” (gzip format), “.bz2” (bzip2 format) or “.lzma” (lzma
format), the stream is assumed to be compressed according to the corresponding
format. A filter task will then be used to process it accordingly if the format is
implemented in Scotch and enabled on your system.
To date, data can be read and written in bzip2 and gzip formats, and can
also be read in the lzma format. Since the compression ratio of lzma on Scotch
graphs is 30% better than the one of gzip and bzip2 (which are almost equivalent
27
External
mesh file
External
graph file
mcv
gcv
mmk_*
gmk_*
Geometry
file
amk_*
.xyz
Source
mesh file
gmk_msh
.msh
mtst
Source
graph file
Target file
amk_grf
.grf
mord
gord
gtst
gmap
Ordering
file
Mapping
file
.ord
.map
gotst
acpl
.tgt
gout
atst
gmtst
File
Graphics
file
Program
Data flow
Figure 12: General architecture of the Scotch project. All of the features offered
by the stand-alone programs are also available in the libScotch library.
28
in this case), the lzma format is a very good choice for handling very large graphs.
To see how to enable compressed data handling in Scotch, please refer to Section 8.
When the compressed format allows it, several files can be provided on
the same stream, and be uncompressed on the fly.
For instance, the
command “cat brol.grf.gz brol.xyz.gz | gout -.gz -.gz -Mn - brol.iv”
concatenates the topology and geometry data of some graph brol and feed them
as a single compressed stream to the standard input of program gout, hence the
”-.gz” to indicate a compressed standard stream.
6.3
6.3.1
Description
acpl
Synopsis
acpl [input target file [output target file]] options
Description
The program acpl is the decomposition-defined architecture file compiler. It
processes architecture files of type “deco 0” built by hand or by the amk *
programs, to create a “deco 1” compiled architecture file of about four times
the size of the original one; see section 5.4.1, page 22, for a detailed description
of decomposition-defined target architecture file formats.
The mapper can read both original and compiled architecture file formats.
However, compiled architecture files are read much more efficiently, as they are
directly loaded into memory without further processing. Since the compilation
time of a target architecture graph evolves as the square of its number of
vertices, precompiling with acpl can save some time when many mappings
are to be performed onto the same large target architecture.
Options
6.3.2
-h
Display the program synopsis.
-V
Print the program version and copyright.
amk *
Synopsis
amk ccc dim [output target file] options
amk fft2 dim [output target file] options
amk hy dim [output target file] options
amk m2 dimX [dimY [output target file]] options
amk p2 weight0 [weight1 [output target file]] options
Description
The amk * programs make target graphs. Each of them is devoted to a
29
specific topology, for which it builds target graphs of any dimension.
These programs are an alternate way between algorithmically-coded built-in
target architectures and decompositions computed by mapping with amk grf.
Like built-in target architectures, their decompositions are algorithmically
computed, and like amk grf, their output is a decomposition-defined target
architecture file. These programs allow the definition and testing of new
algorithmically-coded target architectures without coding them in the core of
the mapper.
Program amk ccc outputs the target architecture file of a Cube-ConnectedCycles graph of dimension dim.
Vertex (l, m) of CCC(dim), with
0 ≤ l < dim and 0 ≤ m < 2dim , is linked to vertices ((l − 1) mod dim, m),
((l + 1) mod dim, m), and (l, m ⊕ 2l ), and is labeled l × 2dim + m. ⊕ denotes
the bitwise exclusive-or binary operator, and a mod b the integer remainder
of the euclidian division of a by b.
Program amk fft2 outputs the target architecture file of a binary FastFourier-Transform graph of dimension dim. Vertex (l, m) of FFT(dim),
with 0 ≤ l ≤ dim and 0 ≤ m < 2dim , is linked to vertices (l − 1, m),
(l − 1, m mod 2l−1 ), (l + 1, m), and (l + 1, m ⊕ 2l ), if they exist, and is labeled
l × 2dim + m.
Program amk hy outputs the target architecture file of a hypercube graph
of dimension dim. Vertices are labeled according to the decimal value of
their binary representation. The decomposition-defined target architectures
computed by amk hy do not exactly give the same results as the built-in
hypercube targets because distances are not computed in the same manner,
although the two recursive bipartitionings are identical. To achieve best
performance and save space, use the built-in architecture.
Program amk p2 outputs the target architecture file of a weighted path graph
with two vertices, the weights of which are given as parameters.
This simple target topology is used to bipartition a source graph into two
weighted parts with as few cut edges as possible. In particular, it is used
to compute independent partitions of the processors of a multi-user parallel
machine. As a matter of fact, if the yet unallocated part of the machine is
represented by a source graph with n vertices, and n′ processors are requested
by a user in order to run a job (with n′ ≤ n), mapping the source graph onto
the weighted path graph with two vertices of weights n′ and n − n′ leads to
a partition of the machine in which the allocated n′ processors should be as
densely connected as possible (see Figure 13).
Options
-h Display the program synopsis.
-mmethod
Select the bipartitioning method (for amk m2 only).
n Nested dissection.
o Dimension-per-dimension one-way dissection. This is less efficient
than nested dissection, and this feature exists only for benchmarking
purposes.
30
a. Construction of a partition with 13
vertices (in black) on a 8 × 8 bidimensional mesh architecture.
b. Construction of a partition with
17 vertices (in black) on the remaining
architecture.
Figure 13: Construction of partitions on a bidimensional 8 × 8 mesh architecture
by weighted bipartitioning.
-V Print the program version and copyright.
6.3.3
amk grf
Synopsis
amk grf [input graph file [output target file]] options
Description
The program amk grf turns a source graph file into a decomposition-defined
target file. It computes a recursive bipartitioning of the source graph, as well
as the array of distances between all pairs of its vertices, both of which are
combined to give a decomposition-defined target architecture of same topology
as the input source graph.
The -l option restricts the target architecture to the vertices indicated in the
given vertex list file. It is therefore possible to build a target architecture
made of several disconnected parts of a bigger architecture. Note that this is
not equivalent to turning a disconnected source graph into a target architecture, since doing so would lead to an architecture made of several independent
pieces at infinite distance one from another. Considering the selected vertices
within their original architecture makes it possible to compute the distance
between vertices belonging to distinct connected components, and therefore
to evaluate the cost of the mapping of two neighbor processes onto disjoint
areas of the architecture.
The restriction feature is very useful in the context of multi-user parallel machines. On these machines, when users request processors in order to run their
jobs, the partitions allocated by the operating system may not be regular nor
connected, because of existing partitions already attributed to other people.
By feeding amk grf with the source graph representing the whole parallel machine, and the vertex list containing the labels of the processors allocated by
the operating system, it is possible to build a target architecture corresponding to this partition, and therefore to map processes on it, automatically,
regardless of the partition shape.
The -b option selects the recursive bipartitioning strategy used to build the
31
decomposition of the source graph. For regular, unweighted, topologies, the
’-b(g|h)fx’ recursive bipartitioning strategy should work best. For irregular
or weighted graphs, use the default strategy, which is more flexible. See
also the manual page of function SCOTCH archBuild, page 67, for further
information.
Options
-bstrategy
Use recursive bipartitioning strategy strategy to build the decomposition of the architecture graph. The format of bipartitioning strategies is
defined within section 7.3.1, at page 55.
-h
Display the program synopsis.
-linput vertex file
Load vertex list from input vertex file. As for all other file names, “-”
may be used to indicate standard input.
-V
6.3.4
Print the program version and copyright.
atst
Synopsis
atst [input target file [output data file]] options
Description
The program atst is the architecture tester. It gives some statistics on
decomposition-defined target architectures, and in particular the minimum,
maximum, and average communication costs (that is, weighted distance) between all pairs of processors.
Options
6.3.5
-h
Display the program synopsis.
-V
Print the program version and copyright.
gcv
Synopsis
gcv [input graph file [output graph file [output geometry file]]] options
Description
The program gcv is the source graph converter. It takes on input a graph
file of the format specified with the -i option, and outputs its equivalent
in the format specified with the -o option, along with its associated geometry file whenever geometry data is available. At the time being, it accepts
four input formats: the Matrix Market format [5], the Harwell-Boeing collection format [10], the Chaco/MeTiS graph format [24], and the Scotch
format. Three output format are available: the Matrix Market format, the
Chaco/MeTiS graph format and the Scotch source graph and geometry
data format.
32
Options
-h
Display the program synopsis.
-iformat
Specify the type of input graph. The available input formats are listed
below.
b[number]
Harwell-Boeing graph collection format. Only symmetric assembled
matrices are currently supported. Since files in this format can contain several graphs one after another, the optional integer number,
starting from 0, indicates which graph of the file is considered for
conversion.
c Chaco v1.0/MeTiS format.
m The Matrix Market format.
s Scotch source graph format.
-oformat
Specify the output graph format. The available output formats are listed
below.
c
m
s
-V
Chaco v1.0/MeTiS format.
The Matrix Market format.
Scotch source graph format.
Print the program version and copyright.
Default option set is “-Ib0 -Os”.
6.3.6
gmap
Synopsis
gmap [input graph file [input target file [output mapping file [output log file]]]]
options
Description
The program gmap is the graph mapper. It uses a partitioning strategy to
map a source graph onto a target graph, so that the weight of source graph
vertices allocated to target vertices is balanced, and the communication cost
function fC is minimized.
The implemented mapping methods mainly derive from graph theory.
In particular, graph geometry is never used, even if it is available; only
topological properties are taken into account. Mapping methods are used to
define mapping strategies by means of selection, combination, grouping, and
condition operators.
The only mapping method implemented in version 5.1 is the Dual Recursive
Bipartitioning algorithm, which uses graph bipartitioning methods. Available bipartitioning methods include a multi-level algorithm that uses other
bipartitioning methods to compute the initial and refined bipartitions, an
improved implementation of the Fiduccia–Mattheyses heuristic designed to
handle weighted graphs, a greedy method derived from the Gibbs, Poole, and
33
Stockmeyer algorithm, the greedy graph growing heuristic, and a greedy “exactifying” refinement algorithm designed to balance vertex loads as much as
possible; random and backtracking methods are also provided.
The -m option allows the user to define the mapping strategy.
If mapping statistics are wanted rather than the mapping output itself, mapping output can be set to /dev/null, with option -vmt to get mapping statistics and timings.
Options
Since the program is devoted to experimental studies, it has many optional
parameters, used to test various execution modes. Values set by default will
give best results in most cases.
-h
Display the program synopsis.
-mstrat
Apply mapping strategy strat. The format of mapping strategies is defined in section 7.3.1.
-sobj
Mask source edge and vertex weights. This option allows the user to “unweight” weighted source graphs by removing weights from edges and vertices at loading time. obj may contain several of the following switches.
e
v
-V
Remove edge weights, if any.
Remove vertex weights, if any.
Print the program version and copyright.
-vverb
Set verbose mode to verb, which may contain several of the following
switches. For a detailed description of the data displayed, please refer to
the manual page of gmtst below.
m
s
t
-V
6.3.7
Mapping information.
Strategy information. This parameter displays the default mapping
strategy used by gmap.
Timing information.
Print the program version and copyright.
gmk *
Synopsis
gmk hy dim [output graph file] options
gmk m2 dimX [dimY [output graph file]] options
gmk m3 dimX [dimY [dimZ [output graph file]]] options
gmk ub2 dim [output graph file] options
Description
The gmk * programs make source graphs. Each of them is devoted to a
specific topology, for which it builds target graphs of any dimension.
34
The gmk * programs are mainly used in conjunction with amk grf. Most
gmk * programs build source graphs describing parallel machines, which
are used by amk grf to generate corresponding target sub-architectures,
by means of its -l option. Such a procedure is shown in section 9, which
builds a target architecture from five vertices of a binary de Bruijn graph of
dimension 3.
Program gmk hy outputs the source file of a hypercube graph of dimension
dim. Vertices are labeled according to the decimal value of their binary
representation.
Program gmk m2 outputs the source file of a bidimensional mesh with dimX
columns and dimY rows. If the -t option is set, tori are built instead of
meshes. The vertex of coordinates (posX, posY ) is labeled posY×dimX+posX.
Program gmk m3 outputs the source file of a tridimensional mesh with dimZ
layers of dimY rows by dimX columns. If the -t option is set, tori are
built instead of meshes. The vertex of coordinates (posX, posY ) is labeled
(posZ × dimY + posY) × dimX + posX.
Program gmk ub2 outputs the source file of a binary unoriented de Bruijn
graph of dimension dim. Vertices are labeled according to the decimal value
of their binary representation.
Options
-goutput geometry file
Output graph geometry to file output geometry file (for gmk m2 only). As
for all other file names, “-” may be used to indicate standard output.
6.3.8
-h
Display the program synopsis.
-t
Build a torus rather than a mesh (for gmk m2 only).
-V
Print the program version and copyright.
gmk msh
Synopsis
gmk msh [input mesh file [output graph file]] options
Description
The gmk msh program builds a graph file from a mesh file. All of the nodes
of the mesh are turned into graph vertices, and edges are created between
all pairs of vertices that share an element (that is, elements are turned into
cliques).
Options
-h
Display the program synopsis.
-V
Print the program version and copyright.
35
6.3.9
gmtst
Synopsis
gmtst
[input graph file
put data file]]]] options
[input target file
[input mapping file
[out-
Description
The program gmtst is the graph mapping tester. It outputs some statistics
on the given mapping, regarding load balance and inter-processor communication.
The two first statistics lines deal with process mapping statistics, while the
following ones deal with communication statistics. The first mapping line
gives the number of processors used by the mapping, followed by the number
of processors available in the architecture, and the ratio of these two numbers,
written between parentheses. The second mapping line gives the minimum,
maximum, and average loads of the processors, followed by the variance of the
load distribution, and an imbalance ratio equal to the maximum load over the
average load. The first communication line gives the minimum and maximum
number of neighbors over all blocks of the mapping, followed by the sum of the
number of neighbors over all blocks of the mapping, that is the total number
of messages that have to be sent to exchange data between all neighboring
blocks. The second communication line gives the average dilation of the edges,
followed by the sum of all edge dilations. The third communication line gives
the average expansion of the edges, followed by the value of function fC . The
fourth communication line gives the average cut of the edges, followed by the
number of cut edges. The fifth communication line shows the ratio of the average expansion over the average dilation; it is smaller than 1 when the mapper
succeeds in putting heavily intercommunicating processes closer to each other
than it does for lightly communicating processes; it is equal to 1 if all edges
have the same weight. The remaining lines form a distance histogram, which
shows the amount of communication load that involves processors located at
increasing distances.
gmtst allows the testing of cross-architecture mappings. By inputing it a
target architecture different from the one that has been used to compute the
mapping, but with compatible vertex labels, one can see what the mapping
would yield on this new target architecture.
Options
-h
Display the program synopsis.
-V
Print the program version and copyright.
6.3.10
gord
Synopsis
gord [input graph file [output ordering file [output log file]]] options
Description
The gord program is the block sparse matrix graph orderer. It uses an ordering strategy to compute block orderings of sparse matrices represented as
36
source graphs, whose vertex weights indicate the number of DOFs per node (if
this number is non homogeneous) and whose edges are unweighted, in order
to minimize fill-in and operation count.
Since its main purpose is to provide orderings that exhibit high concurrency
for parallel block factorization, it comprises a nested dissection method [17],
but classical [41] and state-of-the-art [1, 49] minimum degree algorithms are
implemented as well. Ordering methods are used to define ordering strategies
by means of selection, grouping, and condition operators.
For the nested dissection method, vertex separation methods comprise
algorithms that directly compute vertex separators, as well as methods that
build vertex separators from edge separators, i.e. graph bipartitions (all of
the graph bipartitioning methods available in the static mapper gmap can be
used in this latter case).
The -o option allows the user to define the ordering strategy.
When the graphs to order are very large, the same results can be obtained by
using the dgord parallel program of the PT-Scotch distribution, which can
read centralized graph files too.
Options
Since the program is devoted to experimental studies, it has many optional
parameters, used to test various execution modes. Values set by default will
give best results in most cases.
-h Display the program synopsis.
-moutput mapping file
Write to output mapping file the mapping of graph vertices to column
blocks. All of the separators and leaves produced by the nested dissection
method are considered as distinct column blocks, which may be in turn
split by the ordering methods that are applied to them. Distinct integer
numbers are associated with each of the column blocks, such that the
number of a block is always greater than the ones of its predecessors in
the elimination process, that is, its descendants in the elimination tree.
The structure of mapping files is given in section 5.5.
When the geometry of the graph is available, this mapping file may be
processed by program gout to display the vertex separators and supervariable amalgamations that have been computed.
-ostrat
Apply ordering strategy strat. The format of ordering strategies is defined
in section 7.3.3.
-toutput tree file
Write to output tree file the structure of the separator tree. The data
that is written resembles much the one of a mapping file: after a first
line that contains the number of lines to follow, there are that many lines
of mapping pairs, which associate an integer number with every graph
vertex index. This integer number is the number of the column block
which is the parent of the column block to which the vertex belongs,
or −1 if the column block to which the vertex belongs is a root of the
separator tree (there can be several roots, if the graph is disconnected).
Combined to the column block mapping data produced by option -m, the
tree structure allows one to rebuild the separator tree.
37
Print the program version and copyright.
-V
-vverb
Set verbose mode to verb, which may contain several of the following
switches.
s
t
6.3.11
Strategy information. This parameter displays the default ordering
strategy used by gord.
Timing information.
gotst
Synopsis
gotst [input graph file [input ordering file [output data file]]] options
Description
The program gotst is the ordering tester. It gives some statistics on orderings,
including the number of non-zeros and the operation count of the factored
matrix, as well as statistics regarding the elimination tree. Since it performs
the factorization of the reordered matrix, it can take a very long time and
consume a large amount of memory when applied to large graphs.
The first two statistics lines deal with the elimination tree. The first one
displays the number of leaves, while the second shows the minimum height of
the tree (that is, the length of the shortest path from any leaf to the –or a–
root node), its maximum height, its average height, and the variance of the
heights with respect to the average. The third line displays the number of nonzero terms in the factored matrix, the amount of index data that is necessary
to maintain the block structure of the factored matrix, and the number of
operations required to factor the matrix by means of Cholesky factorization.
Options
-h
Display the program synopsis.
-V
Print the program version and copyright.
6.3.12
gout
Synopsis
gout [input graph file [input geometry file
visualization file]]]] options
[input mapping file
[output
Description
The gout program is the graph, matrix, and mapping viewer program. It takes
on input a source graph, its geometry file, and optionally a mapping result file,
and produces a file suitable for display. At the time being, gout can generate plain and encapsulated PostScript files for the display of adjacency matrix
patterns and the display of planar graphs (although tridimensional objects can
be displayed by means of isometric projection, the display of tridimensional
mappings is not efficient), and Open Inventor files [42] for the interactive
visualization of tridimensional graphs.
In the case of mapping display, the number of mapping pairs contained in the
38
input mapping file may differ from the number of vertices of the input source
graph; only mapping pairs the source labels of which match labels of source
graph vertices will be taken into account for display. This feature allows the
user to show the result of the mapping of a subgraph drawn on the whole
graph, or else to outline the most important aspects of a mapping by restricting the display to a limited portion of the graph. For example, Figure 14.b
shows how the result of the mapping of a subgraph of the bidimensional mesh
M2 (4, 4) onto the complete graph K(2) can be displayed on the whole M2 (4, 4)
graph, and Figure 14.c shows how the display of the same mapping can be
restricted to a subgraph of the original graph.
a. A subgraph of M2 (4, 4) to
be mapped onto K(2).
b. Mapping result displayed
on the full M2 (4, 4) graph.
c.
Mapping result displayed on another subgraph
of M2 (4, 4).
Figure 14: PostScript diplay of a single mapping file with different subgraphs of the
same source graph. Vertices covered with disks of the same color are mapped onto
the same processor.
Options
-gparameters
Geometry parameters.
n
Do not read geometry data. This option can be used in conjunction
with option -om to avoid reading the geometry file when displaying
the pattern of the adjacency matrix associated with the source graph,
since geometry data are not needed in this case. If this option is set,
the geometry file is not read. However, if an output visualization file
name is given in the command line, dummy input geometry file and
input mapping file names must be specified so that the file argument
39
Figure 15: Snapshot of an Open Inventor display of a sphere partitioned into 7
almost equal pieces by mapping onto the complete graph with 7 vertices. Vertices
of same color are mapped onto the same processor.
r
-h
count is correct. In this case, use the “-” parameter to take standard
input as a dummy geometry input stream. In practice, the -om and
-gn options always imply the -mn option.
For bidimensional geometry only, rotate geometry data by 90 degrees, counter-clockwise.
Display the program synopsis.
-mn Do not read mapping data, and display the graph without any mapping
information. If this option is set, the mapping file is not read. However, if
an output visualization file name is given in the command line, a dummy
input mapping file name must be specified so that the file argument count
is correct. In this case, use the “-” parameter to take standard input as
a dummy mapping input stream.
-oformat[{parameters}]
Specify the type of output, with optional parameters within curly braces
and separated by commas. The output formats are listed below.
i
Output the graph in SGI’s Open Inventor format, in ASCII mode,
suitable for display by the ivview program [42]. The optional parameters are given below.
c Color output, using 16 different colors. Opposite of g.
g Grey-level output, using 8 different levels. Opposite of c.
r Remove cut edges. Edges the ends of which are mapped onto
different processors are not displayed. Opposite of v.
v View cut edges. All graph edges are displayed. Opposite of r.
40
Output the pattern of the adjacency matrix associated with the
source graph, in Adobe’s PostScript format. The optional parameters are given below.
e Encapsulated PostScript output, suitable for LATEX use with
epsf. Opposite of f.
f Full-page PostScript output, suitable for direct printing. Opposite of e.
p Output the graph in Adobe’s PostScript format. The optional parameters are given below.
a Avoid displaying the mapping disks. Opposite of d.
c Color PostScript output, using 16 different colors. Opposite of
g.
d Display the mapping disks. Opposite of a.
e Encapsulated PostScript output, suitable for LATEX use with
epsf. Opposite of f.
f Full-page PostScript output, suitable for direct printing. Opposite of e.
g Grey-level PostScript output. Opposite of c.
l Large clipping. Mapping disks are included in the clipping area
computation. Opposite of s.
r Remove cut edges. Edges the ends of which are mapped onto
different processors are not displayed. Opposite of v.
s Small clipping. Mapping disks are excluded from the clipping
area computation. Opposite of l.
v View cut edges. All graph edges are displayed. Opposite of r.
x=val
Minimum X relative clipping position (in [0.0;1.0]).
X=val
Maximum X relative clipping position (in [0.0;1.0]).
y=val
Minimum Y relative clipping position (in [0.0;1.0]).
Y=val
Maximum Y relative clipping position (in [0.0;1.0]).
-V Print the program version and copyright.
m
Default option set is “-Oi{v}”.
6.3.13
gtst
Synopsis
gtst [input graph file [output data file]] options
Description
The program gtst is the source graph tester. It checks the consistency of
the input source graph structure (matching of arcs, number of vertices and
edges, etc.), and gives some statistics regarding edge weights, vertex weights,
and vertex degrees.
41
When the graphs to test are very large, the same results can be obtained by
using the dgtst parallel program of the PT-Scotch distribution, which can
read centralized graph files too.
Options
-h
Display the program synopsis.
-V
Print the program version and copyright.
6.3.14
mcv
Synopsis
mcv [input mesh file [output mesh file [output geometry file]]] options
Description
The program mcv is the source mesh converter. It takes on input a mesh file
of the format specified with the -i option, and outputs its equivalent in the
format specified with the -o option, along with its associated geometry file
whenever geometrical data is available. At the time being, it only accepts one
external input format: the Harwell-Boeing format [10], for square elemental
matrices only. The only output format to date is the Scotch source mesh
and geometry data format.
Options
-h
Display the program synopsis.
-iformat
Specify the type of input mesh. The available input formats are listed
below.
b[number]
Harwell-Boeing mesh collection format. Only symmetric elemental
matrices are currently supported. Since files in this format can contain several meshes one after another, the optional integer number,
starting from 0, indicates which mesh of the file is considered for
conversion.
s Scotch source mesh format.
-oformat
Specify the output graph format. The available output formats are listed
below.
s
-V
Scotch source graph format.
Print the program version and copyright.
Default option set is “-Ib0 -Os”.
6.3.15
mmk *
Synopsis
mmk m2 dimX [dimY [output mesh file]] options
mmk m3 dimX [dimY [dimZ [output mesh file]]] options
42
Description
The mmk * programs make source meshes.
Program mmk m2 outputs the source file of a bidimensional mesh with
dimX × dimY elements and (dimX + 1) × (dimY + 1) nodes. The element
of coordinates (posX, posY ) is labeled posY × dimX + posX.
Program mmk m3 outputs the source file of a tridimensional mesh with
dimX × dimY × dimZ elements and (dimX + 1) × (dimY + 1) × (dimZ + 1)
nodes.
Options
-goutput geometry file
Output mesh geometry to file output geometry file (for mmk m2 only). As
for all other file names, “-” may be used to indicate standard output.
-h
Display the program synopsis.
-V
Print the program version and copyright.
6.3.16
mord
Synopsis
mord [input mesh file [output ordering file [output log file]]] options
Description
The mord program is the block sparse matrix mesh orderer. It uses an ordering
strategy to compute block orderings of sparse matrices represented as source
meshes, whose node vertex weights indicate the number of DOFs per node (if
this number is non homogeneous), in order to minimize fill-in and operation
count.
Since its main purpose is to provide orderings that exhibit high concurrency
for parallel block factorization, it comprises a nested dissection method [17],
but classical [41] and state-of-the-art [1, 49] minimum degree algorithms are
implemented as well. Ordering methods are used to define ordering strategies
by means of selection, grouping, and condition operators.
The -o option allows the user to define the ordering strategy.
Options
Since the program is devoted to experimental studies, it has many optional
parameters, used to test various execution modes. Values set by default will
give best results in most cases.
-h
Display the program synopsis.
-moutput mapping file
Write to output mapping file the mapping of mesh node vertices to column blocks. All of the separators and leaves produced by the nested
dissection method are considered as distinct column blocks, which may
43
be in turn split by the ordering methods that are applied to them. Distinct integer numbers are associated with each of the column blocks, such
that the number of a block is always greater than the ones of its predecessors in the elimination process, that is, its leaves in the elimination
tree. The structure of mapping files is given in section 5.5.
When the coordinates of the node vertices are available, the mapping
file may be processed by program gout, along with the graph structure
that can be created from the source mesh file by means of the gmk
msh program, to display the node vertex separators and supervariable
amalgamations that have been computed.
-ostrat
Apply ordering strategy strat. The format of ordering strategies is defined
in section 7.3.3.
-toutput tree file
Write to output tree file the structure of the separator tree. The data
that is written resembles much the one of a mapping file: after a first
line that contains the number of lines to follow, there are that many
lines of mapping pairs, which associate an integer number with every
node vertex index. This integer number is the number of the column
block which is the parent of the column block to which the node vertex
belongs, or −1 if the column block to which the node vertex belongs is
a root of the separator tree (there can be several roots, if the mesh is
disconnected).
Combined to the column block mapping data produced by option -m, the
tree structure allows one to rebuild the separator tree.
Print the program version and copyright.
-V
-vverb
Set verbose mode to verb, which may contain several of the following
switches.
s
t
6.3.17
Strategy information. This parameter displays the default ordering
strategy used by mord.
Timing information.
mtst
Synopsis
mtst [input mesh file [output data file]] options
Description
The program mtst is the source mesh tester. It checks the consistency of the
input source mesh structure (matching of arcs that link elements to nodes
and nodes to elements, number of elements, nodes, and edges, etc.), and gives
some statistics regarding element and node weights, edge weights, and element
and node degrees.
Options
-h
Display the program synopsis.
-V
Print the program version and copyright.
44
7
Library
All of the features provided by the programs of the Scotch distribution may be
directly accessed by calling the appropriate functions of the libScotch library,
archived in files libscotch.a and libscotcherr.a. These routines belong to six
distinct classes:
• source graph and source mesh handling routines, which serve to declare, build,
load, save, and check the consistency of source graphs and meshes, along with
their geometry data;
• target architecture handling routines, which allow the user to declare, build,
load, and save target architectures;
• strategy handling routines, which allow the user to declare and build mapping
and ordering strategies;
• mapping routines, which serve to declare, compute, and save mappings of
source graphs to target architectures by means of mapping strategies;
• ordering routines, which allow the user to declare, compute, and save orderings
of source graphs and meshes;
• error handling routines, which allow the user either to provide his own error
servicing routines, or to use the default routines provided in the libScotch
distribution.
A MeTiS compatibility library, called libscotchmetis.a, is also available. It
allows users who were previously using MeTiS in their software to take advantage of
the efficieny of Scotch without having to modify their code. The services provided
by this library are described in Section 7.14.
7.1
7.1.1
Calling the routines of libScotch
Calling from C
All of the C routines of the libScotch library are prefixed with “SCOTCH ”. The
remainder of the function names is made of the name of the type of object to which
the functions apply (e.g. “graph”, “mesh”, “arch”, “map”, etc.), followed by the
type of action performed on this object: “Init” for the initialization of the object,
“Exit” for the freeing of its internal structures, “Load” for loading the object from
a stream, and so on.
Typically, functions that return an error code return zero if the function succeeds, and a non-zero value in case of error.
For instance, the SCOTCH graphInit and SCOTCH graphLoad routines, described
in sections 7.5.1 and 7.5.4, respectively, can be called from C by using the following
code.
#include <stdio.h>
#include "scotch.h"
...
SCOTCH_Graph
grafdat;
FILE *
fileptr;
if (SCOTCH_graphInit (&grafdat) != 0) {
45
... /* Error handling */
}
if ((fileptr = fopen ("brol.grf", "r")) == NULL) {
... /* Error handling */
}
if (SCOTCH_graphLoad (&grafdat, fileptr, -1, 0) != 0) {
... /* Error handling */
}
...
Since “scotch.h” uses several system objects which are declared in “stdio.h”,
this latter file must be included beforehand in your application code.
Although the “scotch.h” and “ptscotch.h” files may look very similar on your
system, never mistake them, and always use the “scotch.h” file as the include file
for compiling a program which uses only the sequential routines of the libScotch
library.
7.1.2
Calling from Fortran
The routines of the libScotch library can also be called from Fortran. For any C
function named SCOTCH typeAction() which is documented in this manual, there
exists a SCOTCHFTYPEACTION () Fortran counterpart, in which the separating
underscore character is replaced by an “F”. In most cases, the Fortran routines
have exactly the same parameters as the C functions, save for an added trailing
INTEGER argument to store the return value yielded by the function when the
return type of the C function is not void.
Since all the data structures used in libScotch are opaque, equivalent declarations for these structures must be provided in Fortran. These structures must
therefore be defined as arrays of DOUBLEPRECISIONs, of sizes given in file scotchf.h,
which must be included whenever necessary.
For routines which read or write data using a FILE * stream in C, the Fortran counterpart uses an INTEGER parameter which is the numer of the Unix file
descriptor corresponding to the logical unit from which to read or write. In most
Unix implementations of Fortran, standard descriptors 0 for standard input (logical unit 5), 1 for standard output (logical unit 6) and 2 for standard error are
opened by default. However, for files that are opened using OPEN statements, an
additional function must be used to obtain the number of the Unix file descriptor
from the number of the logical unit. This function is called FNUM in most Unix
implementations of Fortran.
For instance, the SCOTCH graphInit and SCOTCH graphLoad routines, described
in sections 7.5.1 and 7.5.4, respectively, can be called from Fortran by using the
following code.
INCLUDE "scotchf.h"
DOUBLEPRECISION GRAFDAT(SCOTCH_GRAPHDIM)
INTEGER RETVAL
...
CALL SCOTCHFGRAPHINIT (GRAFDAT (1), RETVAL)
IF (RETVAL .NE. 0) THEN
...
OPEN (10, FILE=’brol.grf’)
46
CALL SCOTCHFGRAPHLOAD (GRAFDAT (1), FNUM (10), 1, 0, RETVAL)
CLOSE (10)
IF (RETVAL .NE. 0) THEN
...
Although the “scotchf.h” and “ptscotchf.h” files may look very similar on
your system, never mistake them, and always use the “scotchf.h” file as the include file for compiling a program which uses only the sequential routines of the
libScotch library.
7.1.3
Compiling and linking
The compilation of C or Fortran routines which use routines of the libScotch
library requires that either scotch.h or scotchf.h be included, respectively.
The routines of the libScotch library are grouped in a library file called
libscotch.a. Default error routines that print an error message and exit are provided in library file libscotcherr.a.
Therefore, the linking of applications that make use of the libScotch library with standard error handling is carried out by using the following options:
“-lscotch -lscotcherr -lm”. If you want to handle errors by yourself, you
should not link with library file libscotcherr.a, but rather provide a SCOTCH
errorPrint() routine. Please refer to section 7.12 for more information.
7.1.4
Machine word size issues
Graph indices are represented in Scotch as integer values of type SCOTCH
Num. By default, this type is equivalent to the int C type, that is, an integer type
of size equal to the one of the machine word. However, it can represent any other
integer type. To coerce the length of the Scotch integer type to 32 or 64 bits,
one can use the INTSIZE32 or INTSIZE64 flags, respectively, or else the “-DINT=”
definition, at compile time.
This feature can be used to allow Scotch to handle large graphs on 32-bit
architectures. If the SCOTCH Num type is set to represent a 64-bit integer type,
all graph indices will be 64-bit integers, while function error codes will still be
traditional 32-bit integers.
One must therefore be careful when using the Fortran interface of Scotch.
In the manual pages of the libScotch routines, all Fortran prototypes are given
with both graph indices and return values specified as plain INTEGERs. In practice,
when Scotch is compiled to use 64-bit SCOTCH Nums and 32-bit ints, graph indices
should be declared as INTEGER*8, while integer error codes should still be declared
as INTEGER*4 values.
These discrepancies are not a problem if Scotch is compiled such that all ints
are 64-bit integers. In this case, there is no need to use any type coercing definition.
Also, the MeTiS compatibility library provided by Scotch will not work when
SCOTCH Nums are not ints, since the interface of MeTiS uses regular ints to represent
graph indices. In addition to compile-time warnings, an error message will be issued
when one of these routines is called.
47
7.2
Data formats
All of the data used in the libScotch interface are of integer type SCOTCH Num.
To hide the internals of Scotch to callers, all of the data structures are opaque,
that is, declared within scotch.h as dummy arrays of double precision values, for
the sake of data alignment. Accessor routines, the names of which end in “Size”
and “Data”, allow callers to retrieve information from opaque structures.
In all of the following, whenever arrays are defined, passed, and accessed, it
is assumed that the first element of these arrays is always labeled as baseval,
whether baseval is set to 0 (for C-style arrays) or 1 (for Fortran-style arrays).
Scotch internally manages with base values and array pointers so as to process
these arrays accordingly.
7.2.1
Architecture format
Target architecture structures are completely opaque. The only way to describe an
architecture is by means of a graph passed to the SCOTCH archBuild routine.
7.2.2
Graph format
Source graphs are described by means of adjacency lists. The description of a graph
requires several SCOTCH Num scalars and arrays, as shown in Figures 16 and 17. They
have the following meaning:
baseval
Base value for all array indexings.
vertnbr
Number of vertices in graph.
edgenbr
Number of arcs in graph. Since edges are represented by both of their ends,
the number of edge data in the graph is twice the number of graph edges.
verttab
Array of start indices in edgetab of vertex adjacency sub-arrays.
vendtab
Array of after-last indices in edgetab of vertex adjacency sub-arrays. For any
vertex i, with baseval ≤ i < (baseval+ vertnbr), vendtab[i] − verttab[i]
is the degree of vertex i, and the indices of the neighbors of i are stored in
edgetab from edgetab[verttab[i]] to edgetab[vendtab[i]−1], inclusive.
When all vertex adjacency lists are stored in order in edgetab, it is possible to
save memory by not allocating the physical memory for vendtab. In this case,
illustrated in Figure 16, verttab is of size vertnbr + 1 and vendtab points to
verttab + 1. This case is referred to as the “compact edge array” case, such
that verttab is sorted in ascending order, verttab[baseval] = baseval and
verttab[baseval + vertnbr] = (baseval + edgenbr).
velotab
Optional array, of size vertnbr, holding the integer load associated with every
vertex.
48
baseval
1
vertnbr
7
4 3
1
4
4
2
1
2
1
4 1
edgenbr 24
1
2
2
3
1
vlbltab
velotab
2
3
6
4 1 4 4 4 4 4
3
4
7
4
1
5 4
vendtab
verttab
1 4 10 13 16 19 22 25
edgetab
3 2 6 3 4 1 7 6 5 1 2 4 2 7 3 7 2 6 2 1 5 5 2 4
edlotab
1 1 1 2 2 1 2 3 3 1 2 2 2 1 2 1 3 3 3 1 3 1 2 1
Figure 16: Sample graph and its description by libScotch arrays using a compact
edge array. Numbers within vertices are vertex indices, bold numbers close to
vertices are vertex loads, and numbers close to edges are edge loads. Since the edge
array is compact, verttab is of size vertnbr+1 and vendtab points to verttab+1.
verttab 17 2 13 10 20 27 23
edgetab
3 4 1 7 6 5
2 7 3 1 2 4
3 2 6 7 2 6 5 2 4
2 1 5
2 1 2 1 2 2
1 1 1 1 3 3 1 2 1
3 1 3
vendtab 20 8 16 13 23 30 26
edlotab
2 2 1 2 3 3
Figure 17: Adjacency structure of the sample graph of Figure 16 with disjoint edge
and edge load arrays. Both verttab and vendtab are of size vertnbr. This allows
for the handling of dynamic graphs, the structure of which can evolve with time.
edgetab
Array, of a size equal at least to (maxi (vendtab[i]) − baseval), holding the
adjacency array of every vertex.
edlotab
Optional array, of a size equal at least to (maxi (vendtab[i]) − baseval),
holding the integer load associated with every arc. Matching arcs should
always have identical loads.
Dynamic graphs can be handled elegantly by using the vendtab array. In order
to dynamically manage graphs, one just has to allocate verttab, vendtab and
edgetab arrays that are large enough to contain all of the expected new vertex and
edge data. Original vertices are labeled starting from baseval, leaving free space at
the end of the arrays. To remove some vertex i, one just has to replace verttab[i]
and vendtab[i] with the values of verttab[vertnbr-1] and vendtab[vertnbr-1],
respectively, and browse the adjacencies of all neighbors of former vertex vertnbr-1
such that all (vertnbr-1) indices are turned into is. Then, vertnbr must be
decremented, and SCOTCH graphBuild() must be called to account for the change
of topology. If a graph building routine such as SCOTCH graphLoad() or SCOTCH
49
graphBuild() had already been called on the SCOTCH Graph structure, SCOTCH
graphFree() has to be called first in order to free the internal structures associated
with the older version of the graph, else these data would be lost, which would
result in memory leakage.
To add a new vertex, one has to fill verttab[vertnbr-1] and vendtab[vertnbr
-1] with the starting and end indices of the adjacency sub-array of the new vertex.
Then, the adjacencies of its neighbor vertices must also be updated to account for it.
If free space had been reserved at the end of each of the neighbors, one just has to
increment the vendtab[i] values of every neighbor i, and add the index of the new
vertex at the end of the adjacency sub-array. If the sub-array cannot be extended,
then it has to be copied elsewhere in the edge array, and both verttab[i] and
vendtab[i] must be updated accordingly. With simple housekeeping of free areas
of the edge array, dynamic arrays can be updated with as little data movement as
possible.
7.2.3
Mesh format
Since meshes are basically bipartite graphs, source meshes are also described by
means of adjacency lists. The description of a mesh requires several SCOTCH Num
scalars and arrays, as shown in Figure 18. They have the following meaning:
velmbas
Base value for element indexings.
vnodbas
Base value for node indexings. The base value of the underlying graph,
baseval, is set as min(velmbas, vnodbas).
velmnbr
Number of element vertices in mesh.
vnodnbr
Number of node vertices in mesh. The overall number of vertices in the
underlying graph, vertnbr, is set as velmnbr + vnodnbr.
edgenbr
Number of arcs in mesh. Since edges are represented by both of their ends,
the number of edge data in the mesh is twice the number of edges.
verttab
Array of start indices in edgetab of vertex (that is, both elements and nodes)
adjacency sub-arrays.
vendtab
Array of after-last indices in edgetab of vertex adjacency sub-arrays. For
any element or node vertex i, with baseval ≤ i < (baseval + vertnbr),
vendtab[i] − verttab[i] is the degree of vertex i, and the indices of the
neighbors of i are stored in edgetab from edgetab[verttab[i]] to edgetab
[vendtab[i]−1], inclusive.
When all vertex adjacency lists are stored in order in edgetab, it is possible to
save memory by not allocating the physical memory for vendtab. In this case,
illustrated in Figure 18, verttab is of size vertnbr + 1 and vendtab points to
verttab + 1. This case is referred to as the “compact edge array” case, such
that verttab is sorted in ascending order, verttab[baseval] = baseval and
verttab[baseval + vertnbr] = (baseval + edgenbr).
50
velmbas
1
vnodbas
4
velmnbr
3
vnodnbr
8
4
10
2
5
11
1
edgenbr 24
6
7
vlbltab
3
velotab
8
9
vendtab
verttab
1 5 9 13 14 16 18 20 21 22 23 25
edgetab
5 11 7 6 10 5 11 4 8 9 6 7 2 2 1 1 3 1 3 3 3 2 2 1
Figure 18: Sample mesh and its description by libScotch arrays using a compact
edge array. Numbers within vertices are vertex indices. Since the edge array is
compact, verttab is of size vertnbr + 1 and vendtab points to verttab + 1.
velotab
Array, of size vertnbr, holding the integer load associated with each vertex.
As for graphs, it is possible to handle elegantly dynamic meshes by means of the
verttab and vendtab arrays. There is, however, an additional constraint, which is
that mesh nodes and elements must be ordered consecutively. The solution to fulfill
this constraint in the context of mesh ordering is to keep a set of empty elements
(that is, elements which have no node adjacency attached to them) between the
element and node arrays. For instance, Figure 19 represents a 4-element mesh
with 6 nodes, and such that 4 element vertex slots have been reserved for new
elements and nodes. These slots are empty elements for which verttab[i] equals
vendtab[i], irrespective of these values, since they will not lead to any memory
access in edgetab.
Using this layout of vertices, new nodes and elements can be created by growing
the element and node sub-arrays into the empty element sub-array, by both of
its sides, without having to re-write the whole mesh structure, as illustrated in
Figure 20. Empty elements are transparent to the mesh ordering routines, which
base their work on node vertices only. Users who want to update the arrays of
a mesh that has already been declared using the SCOTCH meshBuild routine must
call SCOTCH meshExit prior to updating the mesh arrays, and then call SCOTCH
meshBuild again after the arrays have been updated, so that the SCOTCH Mesh
structure remains consistent with the new mesh data.
7.2.4
Geometry format
Geometry data is always associated with a graph or a mesh. It is simply made
of a single array of double-precision values which represent the coordinates of the
vertices of a graph, or of the node vertices of a mesh, in vertex order. The fields of
a geometry structure are the following:
dimnnbr
Number of dimensions of the graph or of the mesh, which can be 1, 2, or 3.
51
velmbas 11
vnodbas
1
velmnbr
4
vnodnbr
6
1
11
2
3
12
13
edgenbr 24
14
4
5
6
vlbltab
velotab
verttab
1 2 5 8 9 12 0 0 0 0 13 16 19 22
edgetab 11 11 12 13 11 12 14 13 13 14 12 14 1 2 3 5 2 3 4 5 2 3 6 5
vendtab
2 5 8 9 12 13 0 0 0 0 16 19 22 25
Figure 19: Sample mesh and its description by libScotch arrays, with nodes
numbered first and elements numbered last. In order to allow for dynamic remeshing, empty elements (in grey) have been inserted between existing node and
element vertices.
velmbas
9
vnodbas
1
velmnbr
6
vnodnbr
7
1
9
11
2
7
3
12 10
13
edgenbr 36
4
14
5
6
vlbltab
velotab
verttab 25 2 5 8 27 12 31 0 9 35 13 16 19 22
edgetab
11 12 13 9 10 14 13 1 7 3 14 1 2 7 5 2 7 4 5 2 3 6 5 11 9 13 14 12 10 11 9 12 10 7 3 5
vendtab 27 5 8 9 31 13 35 0 12 38 16 19 22 25
Figure 20: Re-meshing of the mesh of Figure 19. New node vertices have been added
at the end of the vertex sub-array, new elements have been added at the beginning
of the element sub-array, and vertex base values have been updated accordingly.
Node adjacency lists that could not fit in place have been added at the end of the
edge array, and some of the freed space has been re-used for new adjacency lists.
Element adjacency lists do not require moving in this case, as all of the elements
have the name number of nodes.
52
geomtab
Array of coordinates. This is an array of double precision values organized
as an array of (x), or (x,y), or (x,y,z) tuples, according to dimnnbr. Coordinates that are not used (e.g. the “z” coordinates for a 2-dimentional
object) are not allocated. Therefore, the “x” coordinate of some graph
vertex i is located at geomtab[(i - baseval) * dimnnbr + baseval], its
“y” coordinate is located at geomtab[(i - baseval) * dimnnbr + baseval
+ 1] if dimnnbr ≤ 2, and its “z” coordinate is located at geomtab[(i baseval) * dimnnbr + baseval + 2] if dimnnbr = 3. Whenever the geometry is associated with a mesh, only node vertices are considered, so
the “x” coordinate of some mesh node vertex i, with vnodbas ≤ i, is located at geomtab[(i - vnodbas) * dimnnbr + baseval], its “y” coordinate is located at geomtab[(i - vnodbas) * dimnnbr + baseval + 1] if
dimnnbr ≤ 2, and its “z” coordinate is located at geomtab[(i - vnodbas) *
dimnnbr + baseval + 2] if dimnnbr = 3.
7.2.5
Block ordering format
Block orderings associated with graphs and meshes are described by means of block
and permutation arrays, made of SCOTCH Nums, as shown in Figure 21. In order for
all orderings to have the same structure, irrespective of whether they are created
from graphs or meshes, all ordering data indices start from baseval, even when they
refer to a mesh the node vertices of which are labeled from a vnodbas index such
that vnodbas > baseval. Consequently, row indices are related to vertex indices
in memory in the following way: row i is associated with vertex i of the SCOTCH
Graph structure if the ordering was computed from a graph, and with node vertex
i + (vnodbas− baseval) of the SCOTCH Mesh structure if the ordering was computed
from a mesh. Block orderings are made of the following data:
permtab
Array holding the permutation of the reordered matrix. Thus, if k =
permtab[i], then row i of the original matrix is now row k of the reordered
matrix, that is, row i is the k th pivot.
peritab
Inverse permutation of the reordered matrix. Thus, if i = peritab[k], then
row k of the reordered matrix was row i of the original matrix.
cblknbr
Number of column blocks (that is, supervariables) in the block ordering.
rangtab
Array of ranges for the column blocks. Column block c, with baseval ≤ c <
(cblknbr+baseval), contains columns with indices ranging from rangtab[i]
to rangtab[i + 1], exclusive, in the reordered matrix. Indices in rangtab
are based. Therefore, rangtab[baseval] is always equal to baseval, and
rangtab[cblknbr + baseval] is always equal to vertnbr + baseval for
graphs and to vnodnbr + baseval for meshes. In order to avoid memory
errors when column blocks are all single columns, the size of rangtab must
always be one more than the number of columns, that is, vertnbr + 1 for
graphs and vnodnbr + 1 for meshes.
treetab
Array of ascendants of permuted column blocks in the separators tree.
53
permtab
2 3 10 6 4 11 8 7 1 12 5 9
peritab
9 1 2 5 11 4 8 7 12 3 6 10
cblknbr
7
1
2
3
4
2 2
5
6
7
8
4
10
3
6
5
7
11
rangtab
1 2 4 5 6 8 10 13
treetab
3 3 7 6 6 7 −1
9
10
11
12
1 1
8
7
5
9
6
3
12
4
Figure 21: Arrays resulting from the ordering by complete nested dissection of a 4
by 3 grid based from 1. Leftmost grid is the original grid, and righmost grid is the
reordered grid, with separators shown and column block indices written in bold.
treetab[i] is the index of the father of column block i in the separators
tree, or −1 if column block i is the root of the separators tree. Whenever separators or leaves of the separators tree are split into subblocks, as the block
splitting, minimum fill or minimum degree methods do, all subblocks of the
same level are linked to the column block of higher index belonging to the
closest separator ancestor. Indices in treetab are based, in the same way as
for the other blocking structures. See Figure 21 for a complete example.
7.3
Strategy strings
The behavior of the mapping and block ordering routines of the libScotch library
is parametrized by means of strategy strings, which describe how and when given
partitioning or ordering methods should be applied to graphs and subgraphs, or to
meshes and submeshes.
7.3.1
Mapping strategy strings
At the time being, mapping methods only apply to graphs, as there is not yet a mesh
mapping tool in the Scotch package. Mapping strategies are made of methods,
with optional parameters enclosed between curly braces, and separated by commas,
in the form of method [{parameters}] . The currently available mapping methods
are the following.
b
Dual Recursive Bipartitioning mapping algorithm, as defined in section 3.1.3.
The parameters of the DRB mapping method are listed below.
job=tie
The tie flag defines how new jobs are stored in job pools.
t
u
Tie job pools together. Subjobs are stored in same pool as their parent job. This is the default behavior, as it proves the most efficient
in practice.
Untie job pools. Subjobs are stored in the next job pool to be processed.
map=tie
The tie flag defines how results of bipartitioning jobs are propagated to
jobs still in pools.
t
Tie both mapping tables together. Results are immediately available
to jobs in the same job pool. This is the default behavior.
54
u
Untie mapping tables. Results are only available to jobs of next pool
to be processed.
poli=policy
Select jobs according to policy policy. Job selection policies define how
bipartitioning jobs are ordered within the currently active job pool. Valid
policy flags are
L
l
r
S
s
Most neighbors of higher level.
Highest level.
Random.
Most neighbors of smaller size. This is the default behavior.
Biggest size.
strat=strat
Apply bipartitioning strategy strat to each bipartitioning job. A bipartitioning strategy is made of one or several bipartitioning methods, which
can be combined by means of strategy operators. Graph bipartitioning
strategies are described below.
7.3.2
Graph bipartitioning strategy strings
A graph bipartitioning strategy is made of one or several graph bipartitioning methods, which can be combined by means of strategy operators. Strategy operators are
listed below, by increasing precedence.
strat1 |strat2
Selection operator. The result of the selection is the best bipartition of the
two that are obtained by the separate application of strat1 and strat2 to the
current bipartition.
strat1 strat2
Combination operator. Strategy strat2 is applied to the bipartition resulting
from the application of strategy strat1 to the current bipartition. Typically,
the first method used should compute an initial bipartition from scratch, and
every following method should use the result of the previous one at its starting
point.
(strat )
Grouping operator. The strategy enclosed within the parentheses is treated
as a single bipartitioning method.
/cond ?strat1 [:strat2];
Condition operator. According to the result of the evaluation of condition
cond, either strat1 or strat2 (if it is present) is applied. The condition applies
to the characteristics of the current active graph, and can be built from logical
and relational operators. Conditional operators are listed below, by increasing
precedence.
cond1 |cond2
Logical or operator. The result of the condition is true if cond1 or cond2
are true, or both.
cond1 &cond2
Logical and operator. The result of the condition is true only if both
cond1 and cond2 are true.
55
!cond
Logical not operator. The result of the condition is true only if cond is
false.
var relop val
Relational operator, where var is a graph variable, val is either a graph
variable or a constant of the type of variable var , and relop is one of ’<’,
’=’, and ’>’. The graph variables are listed below, along with their types.
deg
The average degree of the current graph. Float.
edge
The number of arcs (which is twice the number of edges) of the
current graph. Integer.
load
The overall vertex load (weight) of the current graph. Integer.
load0
The vertex load of the first subset of the current bipartition of the
current graph. Integer.
vert
The number of vertices of the current graph. Integer.
method [{parameters}]
Bipartitioning method. For bipartitioning methods that can be parametrized,
parameter settings may be provided after the method name. Parameters must
be separated by commas, and the whole list be enclosed between curly braces.
The currently available graph bipartitioning methods are the following.
b
Band method. This method builds a band graph of given width around the
current frontier of the graph to which it is applied, and calls a graph bipartitioning strategy to refine the equivalent bipartition of the band graph. Then,
the refined frontier of the band graph is projected back to the current graph.
This method, presented in [8], was created to reduce the cost of vertex separator refinement algorithms in a multi-level context, but it improves partition
quality too. The same behavior is observed for graph bipartitioning. The
parameters of the band bipartitioning method are listed below.
bnd=strat
Set the graph bipartitioning strategy to be used on the band graph.
org=strat
Set the fallback graph bipartitioning strategy to be used on the original
graph if the band graph strategy could not be used. The three cases
which require the use of this fallback strategy are the following. First, if
the separator of the original graph is empty, which makes it impossible
to compute a band graph. Second, if any part of the band graph to be
built is of the same size as the one of the original graph. Third, if the
application of the bnd bipartitioning method to the band graph leads to
a situation where both anchor vertices are placed in the same part.
width=val
Set the width of the band graph. All graph vertices that are at a distance
less than or equal to val from any frontier vertex are kept in the band
graph.
56
d
Diffusion method. This method, presented in [44], flows two kinds of antagonistic liquids, scotch and anti-scotch, from two source vertices, and sets the
new frontier as the limit between vertices which contain scotch and the ones
which contain anti-scotch. Because selecting the source vertices is essential
to the obtainment of useful results, this method has been hard-coded so that
the two source vertices are the two vertices of highest indices, since in the
band method these are the anchor vertices which represent all of the removed
vertices of each part. Therefore, this method must be used on band graphs
only, or on specifically crafted graphs. Applying it to any other graphs is
very likely to lead to extremely poor results. The parameters of the diffusion
bipartitioning method are listed below.
dif=rat
Fraction of liquid which is diffused to neighbor vertices at each pass. To
achieve convergence, the sum of the dif and rem parameters must be
equal to 1, but in order to speed-up the diffusion process, other combinations of higher sum can be tried. In this case, the number of passes
must be kept low, to avoid numerical overflows which would make the
results useless.
pass=nbr
Set the number of diffusion sweeps performed by the algorithm. This
number depends on the width of the band graph to which the diffusion
method is applied. Useful values range from 30 to 500 according to
chosen dif and rem coefficients.
rem=rat
Fraction of liquid which remains on vertices at each pass. See above.
f
Fiduccia-Mattheyses method. The parameters of the Fiduccia-Mattheyses
method are listed below.
bal=rat
Set the maximum weight imbalance ratio to the given fraction of the
subgraph vertex weight. Common values are around 0.01, that is, one
percent.
move=nbr
Maximum number of hill-climbing moves that can be performed before a
pass ends. During each of its passes, the Fiduccia-Mattheyses algorithm
repeatedly swaps vertices between the two parts so as to minimize the
cost function. A pass completes either when all of the vertices have been
moved once, or if too many swaps that do not decrease the value of the
cost function have been performed. Setting this value to zero turns the
Fiduccia-Mattheyses algorithm into a gradient-like method, which may
be used to quickly refine partitions during the uncoarsening phase of the
multi-level method.
pass=nbr
Set the maximum number of optimization passes performed by the algorithm. The Fiduccia-Mattheyses algorithm stops as soon as a pass has
not yielded any improvement of the cost function, or when the maximum
number of passes has been reached. Value −1 stands for an infinite number of passes, that is, as many as needed by the algorithm to converge.
g
Gibbs-Poole-Stockmeyer method. This method has only one parameter.
57
pass=nbr
Set the number of sweeps performed by the algorithm.
h
Greedy-graph-growing method. This method has only one parameter.
pass=nbr
Set the number of runs performed by the algorithm.
m
Multi-level method. The parameters of the multi-level method are listed below.
asc=strat
Set the strategy that is used to refine the partitions obtained at ascending levels of the uncoarsening phase by projection of the bipartitions
computed for coarser graphs. This strategy is not applied to the coarsest
graph, for which only the low strategy is used.
low=strat
Set the strategy that is used to compute the partition of the coarsest
graph, at the lowest level of the coarsening process.
rat=rat
Set the threshold maximum coarsening ratio over which graphs are no
longer coarsened. The ratio of any given coarsening cannot be less that
0.5 (case of a perfect matching), and cannot be greater than 1.0. Coarsening stops when either the coarsening ratio is above the maximum coarsening ratio, or the graph has fewer vertices than the minimum number
of vertices allowed.
type=type
Set the type of matching that is used to coarsen the graphs. type is h for
heavy-edge matching, or s for scan (first-fit) matching.
vert=nbr
Set the threshold minimum graph size under which graphs are no longer
coarsened. Coarsening stops when either the coarsening ratio is above
the maximum coarsening ratio, or the graph has fewer vertices than the
minimum number of vertices allowed.
x
Exactifying method.
z
Zero method. This method moves all of the vertices to the first part. Its
main use is to stop the bipartitioning process, if some condition is true, when
mapping onto variable-sized architectures (see section 3.1.7).
7.3.3
Ordering strategy strings
Ordering strategies are available both for graphs and for meshes. An ordering
strategy is made of one or several ordering methods, which can be combined by
means of strategy operators. The strategy operators that can be used in ordering
strategies are listed below, by increasing precedence.
(strat )
Grouping operator. The strategy enclosed within the parentheses is treated
as a single ordering method.
58
/cond ?strat1 [:strat2];
Condition operator. According to the result of the evaluation of condition
cond, either strat1 or strat2 (if it is present) is applied. The condition applies
to the characteristics of the current node of the separators tree, and can be
built from logical and relational operators. Conditional operators are listed
below, by increasing precedence.
cond1 |cond2
Logical or operator. The result of the condition is true if cond1 or cond2
are true, or both.
cond1 &cond2
Logical and operator. The result of the condition is true only if both
cond1 and cond2 are true.
!cond
Logical not operator. The result of the condition is true only if cond is
false.
var relop val
Relational operator, where var is a node variable, val is either a node
variable or a constant of the type of variable var, and relop is one of ’<’,
’=’, and ’>’. The node variables are listed below, along with their types.
edge
The number of vertices of the current subgraph. Integer.
levl
The level of the subgraph in the separators tree, starting from zero
for the initial graph at the root of the tree. Integer.
load
The overall vertex load (weight) of the current subgraph. Integer.
mdeg
The maximum degree of the current subgraph. Integer.
vert
The number of vertices of the current subgraph. Integer.
method [{parameters}]
Graph or mesh ordering method. Available ordering methods are listed below.
The currently available ordering methods are the following.
b
Blocking method. This method does not perform ordering by itself, but is used
as post-processing to cut into blocks of smaller sizes the separators or large
blocks produced by other ordering methods. This is not useful in the context of
direct solving methods, because the off-diagonal blocks created by the splitting
of large diagonal blocks are likely to be filled at factoring time. However, in
the context of incomplete solving methods such as ILU(k) [29], it can lead
to a significant reduction of the required memory space and time, because it
helps carving large triangular blocks. The parameters of the blocking method
are described below.
cmin=size
Set the minimum size of the resulting subblocks, in number of columns.
Blocks larger than twice this minimum size are cut into sub-blocks of
equal sizes (within one), having a number of columns comprised between
59
size and 2size.
The definition of size depends on the size of the graph to order. Large
graphs cannot afford very small values, because the number of blocks
becomes much too large and limits the acceleration of BLAS 3 routines,
while large values do not help reducing enough the complexity of ILU(k)
solving.
strat=strat
Ordering strategy to be performed. After the ordering strategy is applied,
the resulting separators tree is traversed and all of the column blocks
that are larger than 2size are split into smaller column blocks, without
changing the ordering that has been computed.
c
Compression method [2]. The parameters of the compression method are
listed below.
rat=rat
Set the compression ratio over which graphs and meshes will not be
compressed. Useful values range between 0.7 and 0.8.
cpr=strat
Ordering strategy to use on the compressed graph or mesh if its size is
below the compression ratio times the size of the original graph or mesh.
unc=strat
Ordering strategy to use on the original graph or mesh if the size of the
compressed graph or mesh were above the compression ratio times the
size of the original graph or mesh.
d
Block Halo Approximate Minimum Degree method [49]. The parameters of
the Halo Approximate Minimum Degree method are listed below. The Block
Halo Approximate Minimum Fill method, described below, is more efficient
and should be preferred.
cmin=size
Minimum number of columns per column block. All column blocks of
width smaller than size are amalgamated to their parent column block in
the elimination tree, provided that it does not violate the cmax constraint.
cmax=size
Maximum number of column blocks over which some column block will
not amalgamate one of its descendents in the elimination tree. This
parameter is mainly designed to provide an upper bound for block size
in the context of BLAS3 computations ; else, a huge value should be
provided.
frat=rat
Fill-in ratio over which some column block will not amalgamate one of
its descendents in the elimination tree. Typical values range from 0.05
to 0.10.
f
Block Halo Approximate Minimum Fill method. The parameters of the Halo
Approximate Minimum Fill method are listed below.
cmin=size
Minimum number of columns per column block. All column blocks of
width smaller than size are amalgamated to their parent column block in
the elimination tree, provided that it does not violate the cmax constraint.
60
cmax=size
Maximum number of column blocks over which some column block will
not amalgamate one of its descendents in the elimination tree. This
parameter is mainly designed to provide an upper bound for block size
in the context of BLAS3 computations ; else, a huge value should be
provided.
frat=rat
Fill-in ratio over which some column block will not amalgamate one of
its descendents in the elimination tree. Typical values range from 0.05
to 0.10.
g
Gibbs-Poole-Stockmeyer method. This method is used on separators to reduce
the number and extent of extra-diagonal blocks. If the number of extradiagonal blocks is not relevant, the s method should be preferred. This method
has only one parameter.
pass=nbr
Set the number of sweeps performed by the algorithm.
n
Nested dissection method. The parameters of the nested dissection method
are given below.
ole=strat
Set the ordering strategy that is used on every leaf of the separators tree
if the node separation strategy sep has failed to separate it further.
ose=strat
Set the ordering strategy that is used on every separator of the separators
tree.
sep=strat
Set the node separation strategy that is used on every leaf of the separators tree to make it grow. Node separation strategies are described
below, in section 7.3.4.
s
Simple method. Vertices are ordered in their natural order. This method is
fast, and should be used to order separators if the number of extra-diagonal
blocks is not relevant ; else, the g method should be preferred.
v
Mesh-to-graph method. Available only for mesh ordering strategies. From the
mesh to which this method applies is derived a graph, such that a graph vertex
is associated with every node of the mesh, and a clique is created between all
vertices which represent nodes that belong to the same element. A graph
ordering strategy is then applied to the derived graph, and this ordering is
projected back to the nodes of the mesh. This method is here for evaluation
purposes only, as mesh ordering methods are generally more efficient than
their graph ordering counterpart.
strat=strat
Graph ordering strategy to apply to the associated graph.
7.3.4
Node separation strategy strings
A node separation strategy is made of one or several node separation methods,
which can be combined by means of strategy operators. Strategy operators are
listed below, by increasing precedence.
61
strat1 |strat2
Selection operator. The result of the selection is the best vertex separator of
the two that are obtained by the distinct application of strat1 and strat2 to
the current separator.
strat1 strat2
Combination operator. Strategy strat2 is applied to the vertex separator
resulting from the application of strategy strat1 to the current separator.
Typically, the first method used should compute an initial separation from
scratch, and every following method should use the result of the previous one
as a starting point.
(strat )
Grouping operator. The strategy enclosed within the parentheses is treated
as a single separation method.
/cond ?strat1 [:strat2];
Condition operator. According to the result of the evaluation of condition
cond, either strat1 or strat2 (if it is present) is applied. The condition applies
to the characteristics of the current subgraph, and can be built from logical
and relational operators. Conditional operators are listed below, by increasing
precedence.
cond1 |cond2
Logical or operator. The result of the condition is true if cond1 or cond2
are true, or both.
cond1 &cond2
Logical and operator. The result of the condition is true only if both
cond1 and cond2 are true.
!cond
Logical not operator. The result of the condition is true only if cond is
false.
var relop val
Relational operator, where var is a graph or node variable, val is either
a graph or node variable or a constant of the type of variable var , and
relop is one of ’<’, ’=’, and ’>’. The graph and node variables are listed
below, along with their types.
levl
The level of the subgraph in the separators tree, starting from zero
at the root of the tree. Integer.
proc
The number of processors on which the current subgraph is distributed at this level of the separators tree. This variable is available
only when calling from routines of the PT-Scotch parallel library.
Integer.
rank
The rank of the current processor among the group of processors
on which the current subgraph is distributed at this level of the
separators tree. This variable is available only when calling from
routines of the PT-Scotch parallel library, for instance to decide
which node separation strategy should be used on which processor
in a multi-sequential approach. Integer.
62
vert
The number of vertices of the current subgraph. Integer.
The currently available vertex separation methods are the following.
b
Band method. Available only for graph separation strategies. This method
builds a band graph of given width around the current separator of the graph
to which it is applied, and calls a graph separation strategy to refine the
equivalent separator of the band graph. Then, the refined separator of the
band graph is projected back to the current graph. This method, presented
in [8], was created to reduce the cost of separator refinement algorithms in a
multi-level context, but it improves partition quality too. The parameters of
the band separation method are listed below.
bnd=strat
Set the vertex separation strategy to be used on the band graph.
org=strat
Set the fallback vertex separation strategy to be used on the original
graph if the band graph strategy could not be used. The three cases
which require the use of this fallback strategy are the following. First, if
the separator of the original graph is empty, which makes it impossible
to compute a band graph. Second, if any part of the band graph to be
built is of the same size as the one of the original graph. Third, if the
application of the bnd vertex separation method to the band graph leads
to a situation where both anchor vertices are placed in the same part.
width=val
Set the width of the band graph. All graph vertices that are at a distance
less than or equal to val from any separator vertex are kept in the band
graph.
e
Edge-separation method. Available only for graph separation strategies. This
method builds vertex separators from edge separators, by the method proposed by Pothen and Fang [50], which uses a variant of the Hopcroft and
Karp algorithm due to Duff [9]. This method is expensive and most often
yields poorer results than direct vertex-oriented methods such as the vertex
vertex Greedy-graph-growing and the vertex Fiduccia-Mattheyses algorithms.
The parameters of the edge-separation method are listed below.
bal=val
Set the load imbalance tolerance to val, which is a floating-point ratio
expressed with respect to the ideal load of the partitions.
strat=strat
Set the graph bipartitioning strategy that is used to compute the edge bipartition. The syntax of bipartitioning strategy strings is defined within
section 7.3.2, at page 55.
width=type
Select the width of the vertex separators built from edge separators.
When type is set to f, fat vertex separators are built, that hold all of
the ends of the edges of the edge cut. When it is set to t, a thin vertex
separator is built by removing as many vertices as possible from the fat
separator.
63
f
Vertex Fiduccia-Mattheyses method. The parameters of the vertex FiducciaMattheyses method are listed below.
bal=rat
Set the maximum weight imbalance ratio to the given fraction of the
weight of all node vertices. Common values are around 0.01, that is, one
percent.
move=nbr
Maximum number of hill-climbing moves that can be performed before
a pass ends. During each of its passes, the vertex Fiduccia-Mattheyses
algorithm repeatedly moves vertices from the separator to any of the two
parts, so as to minimize the size of the separator. A pass completes either
when all of the vertices have been moved once, or if too many swaps that
do not decrease the size of the separator have been performed.
pass=nbr
Set the maximum number of optimization passes performed by the algorithm. The vertex Fiduccia-Mattheyses algorithm stops as soon as a
pass has not yielded any reduction of the size of the separator, or when
the maximum number of passes has been reached. Value -1 stands for an
infinite number of passes, that is, as many as needed by the algorithm
to converge.
g
Gibbs-Poole-Stockmeyer method. Available only for graph separation strategies. This method has only one parameter.
pass=nbr
Set the number of sweeps performed by the algorithm.
h
Vertex greedy-graph-growing method. This method has only one parameter.
pass=nbr
Set the number of runs performed by the algorithm.
m
Vertex multi-level method. The parameters of the vertex multi-level method
are listed below.
asc=strat
Set the strategy that is used to refine the vertex separators obtained at
ascending levels of the uncoarsening phase by projection of the separators
computed for coarser graphs or meshes. This strategy is not applied to
the coarsest graph or mesh, for which only the low strategy is used.
low=strat
Set the strategy that is used to compute the vertex separator of the
coarsest graph or mesh, at the lowest level of the coarsening process.
rat=rat
Set the threshold maximum coarsening ratio over which graphs or meshes
are no longer coarsened. The ratio of any given coarsening cannot be less
that 0.5 (case of a perfect matching), and cannot be greater than 1.0.
Coarsening stops when either the coarsening ratio is above the maximum
coarsening ratio, or the graph or mesh has fewer node vertices than the
minimum number of vertices allowed.
64
vert=nbr
Set the threshold minimum size under which graphs or meshes are no
longer coarsened. Coarsening stops when either the coarsening ratio is
above the maximum coarsening ratio, or the graph or mesh has fewer
node vertices than the minimum number of vertices allowed.
t
Thinner method. Available only for graph separation strategies. This method
quickly eliminates all useless vertices of the current separator. It searches the
separator for vertices that have no neighbors in one of the two parts, and
moves these vertices to the part they are connected to. This method may
be used to refine separators during the uncoarsening phase of the multi-level
method, and is faster than a vertex Fiduccia-Mattheyses algorithm with {move
=0}.
v
Mesh-to-graph method. Available only for mesh separation strategies. From
the mesh to which this method applies is derived a graph, such that a graph
vertex is associated with every node of the mesh, and a clique is created
between all vertices which represent nodes that belong to the same element.
A graph separation strategy is then applied to the derived graph, and the
separator is projected back to the nodes of the mesh. This method is here
for evaluation purposes only, as mesh separation methods are generally more
efficient than their graph separation counterpart.
strat=strat
Graph separation strategy to apply to the associated graph.
w
Graph separator viewer. Available only for graph separation strategies. Every call to this method results in the creation, in the current subdirectory,
of partial mapping files called “vgraphseparatevw output nnnnnnnn.map”,
where “nnnnnnnn” are increasing decimal numbers, which contain the current state of the two parts and the separator. These mapping files can be
used as input by the gout program to produce displays of the evolving shape
of the current separator and parts. This is mostly a debugging feature, but
it can also have an illustrative interest. While it is only available for graph
separation strategies, mesh separation strategies can indirectly use it through
the mesh-to-graph separation method.
z
Zero method. This method moves all of the node vertices to the first part,
resulting in an empty separator. Its main use is to stop the separation process
whenever some condition is true.
7.4
7.4.1
Target architecture handling routines
SCOTCH archInit
Synopsis
int SCOTCH archInit (SCOTCH Arch *
archptr)
scotchfarchinit (doubleprecision (*)
integer
Description
65
archdat,
ierr)
The SCOTCH archInit function initializes a SCOTCH Arch structure so as to
make it suitable for future operations. It should be the first function to be
called upon a SCOTCH Arch structure. When the target architecture data is
no longer of use, call function SCOTCH archExit to free its internal structures.
Return values
SCOTCH archInit returns 0 if the graph structure has been successfully initialized, and 1 else.
7.4.2
SCOTCH archExit
Synopsis
void SCOTCH archExit (SCOTCH Arch *
archptr)
scotchfarchexit (doubleprecision (*)
archdat)
Description
The SCOTCH archExit function frees the contents of a SCOTCH Arch structure
previously initialized by SCOTCH archInit. All subsequent calls to SCOTCH
arch routines other than SCOTCH archInit, using this structure as parameter,
may yield unpredictable results.
7.4.3
SCOTCH archLoad
Synopsis
int SCOTCH archLoad (SCOTCH Arch *
FILE *
archptr,
stream)
scotchfarchload (doubleprecision (*)
integer
integer
archdat,
fildes,
ierr)
Description
The SCOTCH archLoad routine fills the SCOTCH Arch structure pointed to by
archptr with the source graph description available from stream stream in
the Scotch target architecture format (see Section 5.4).
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the architecture file.
Return values
SCOTCH archLoad returns 0 if the target architecture structure has been successfully allocated and filled with the data read, and 1 else.
66
7.4.4
SCOTCH archSave
Synopsis
int SCOTCH archSave (const SCOTCH Arch *
FILE *
scotchfarchsave (doubleprecision (*)
integer
integer
archptr,
stream)
archdat,
fildes,
ierr)
Description
The SCOTCH archSave routine saves the contents of the SCOTCH Arch structure
pointed to by archptr to stream stream, in the Scotch target architecture
format (see section 5.4).
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the architecture file.
Return values
SCOTCH archSave returns 0 if the graph structure has been successfully written to stream, and 1 else.
7.4.5
SCOTCH archBuild
Synopsis
int SCOTCH archBuild (SCOTCH Arch *
const SCOTCH Graph *
const SCOTCH Num
const SCOTCH Num *
const SCOTCH Strat *
scotchfarchbuild (doubleprecision (*)
doubleprecision (*)
integer
integer (*)
doubleprecision (*)
integer
archptr,
grafptr,
listnbr,
listtab,
straptr)
archdat,
grafdat,
listnbr,
listtab,
stradat,
ierr)
Description
The SCOTCH archBuild routine fills the architecture structure pointed to by
archptr with the decomposition-defined target architecture computed by applying the graph bipartitioning strategy pointed to by straptr to the architecture graph pointed to by grafptr.
When listptr is not NULL and listnbr is greater than zero, the
decomposition-defined architecture is restricted to the listnbr vertices whose
indices are given in the array pointed to by listtab, from listtab[0] to
listtab[listnbr - 1]. These indices should have the same base value as
67
the one of the graph pointed to by grafptr, that is, be in the range from 0 to
vertnbr − 1 if the graph base is 0, and from 1 to vertnbr if the graph base
is 1.
Graph bipartitioning strategies are declared by means of the SCOTCH strat
GraphBipart function, described in page 102. The syntax of bipartitioning
strategy strings is defined in section 7.3.1, page 55. Additional information
may be obtained from the manual page of amk grf, the stand-alone executable
that uses function SCOTCH archBuild to build decomposition-defined target
architecture from source graphs, available at page 31.
Return values
SCOTCH archBuild returns 0 if the decomposition-defined architecture has
been successfully computed, and 1 else.
7.4.6
SCOTCH archCmplt
Synopsis
int SCOTCH archCmplt (SCOTCH Arch *
const SCOTCH Num
archptr,
vertnbr)
scotchfarchcmplt (doubleprecision (*)
integer
integer
archdat,
vertnbr,
ierr)
Description
The SCOTCH archCmplt routine fills the SCOTCH Arch structure pointed to by
archptr with the description of a complete graph architecture with vertnbr
processors, which can be used as input to SCOTCH graphMap to perform graph
partitioning. A shortcut to this is to use the SCOTCH graphPart routine.
Return values
SCOTCH archCmplt returns 0 if the complete graph target architecture has
been successfully built, and 1 else.
7.4.7
SCOTCH archCmpltw
Synopsis
int SCOTCH archCmpltw (SCOTCH Arch *
const SCOTCH Num
const SCOTCH Num * const
scotchfarchcmplt (doubleprecision (*)
integer
integer (*)
integer
Description
68
archdat,
vertnbr,
velotab,
ierr)
archptr,
vertnbr,
velotab)
The SCOTCH archCmpltw routine fills the SCOTCH Arch structure pointed to
by archptr with the description of a weighted complete graph architecture
with vertnbr processors. The relative weights of the processors are given in
the velotab array. Once the target architecture has been created, it can be
used as input to SCOTCH graphMap to perform weighted graph partitioning.
Return values
SCOTCH archCmpltw returns 0 if the weighted complete graph target architecture has been successfully built, and 1 else.
7.4.8
SCOTCH archName
Synopsis
const char * SCOTCH archName (const SCOTCH Arch *
scotchfarchname (doubleprecision (*)
character (*)
integer
archptr)
archdat,
chartab,
charnbr)
Description
The SCOTCH archName function returns a string containing the name of the
architecture pointed to by archptr. Since Fortran routines cannot return
string pointers, the scotchfarchname routine takes as second and third parameters a character() array to be filled with the name of the architecture,
and the integer size of the array, respectively. If the array is of sufficient
size, a trailing nul character is appended to the string to materialize the end
of the string (this is the C style of handling character strings).
Return values
SCOTCH archName returns a non-null character pointer that points to a nullterminated string describing the type of the architecture.
7.4.9
SCOTCH archSize
Synopsis
SCOTCH Num SCOTCH archSize (const SCOTCH Arch *
scotchfarchsize (doubleprecision (*)
integer
archptr)
archdat,
archnbr)
Description
The SCOTCH archSize function returns the number of nodes of the given target architecture. The Fortran routine has a second parameter, of integer type,
which is set on return with the number of nodes of the target architecture.
Return values
SCOTCH archSize returns the number of nodes of the target architecture.
69
7.5
7.5.1
Graph handling routines
SCOTCH graphInit
Synopsis
int SCOTCH graphInit (SCOTCH Graph *
scotchfgraphinit (doubleprecision (*)
integer
grafptr)
grafdat,
ierr)
Description
The SCOTCH graphInit function initializes a SCOTCH Graph structure so as to
make it suitable for future operations. It should be the first function to be
called upon a SCOTCH Graph structure. When the graph data is no longer of
use, call function SCOTCH graphExit to free its internal structures.
Return values
SCOTCH graphInit returns 0 if the graph structure has been successfully initialized, and 1 else.
7.5.2
SCOTCH graphExit
Synopsis
void SCOTCH graphExit (SCOTCH Graph *
scotchfgraphexit (doubleprecision (*)
grafptr)
grafdat)
Description
The SCOTCH graphExit function frees the contents of a SCOTCH Graph structure previously initialized by SCOTCH graphInit. All subsequent calls to
SCOTCH graph routines other than SCOTCH graphInit, using this structure
as parameter, may yield unpredictable results.
7.5.3
SCOTCH graphFree
Synopsis
void SCOTCH graphFree (SCOTCH Graph *
scotchfgraphfree (doubleprecision (*)
grafptr)
grafdat)
Description
The SCOTCH graphFree function frees the graph data of a SCOTCH Graph structure previously initialized by SCOTCH graphInit, but preserves its internal
70
data structures. This call is equivalent to a call to SCOTCH graphExit immediately followed by a call to SCOTCH graphInit. Consequently, the given
SCOTCH Graph structure remains ready for subsequent calls to any routine of
the libScotch library.
7.5.4
SCOTCH graphLoad
Synopsis
int SCOTCH graphLoad (SCOTCH Graph *
FILE *
SCOTCH Num
SCOTCH Num
scotchfgraphload (doubleprecision (*)
integer
integer
integer
integer
grafptr,
stream,
baseval,
flagval)
grafdat,
fildes,
baseval,
flagval,
ierr)
Description
The SCOTCH graphLoad routine fills the SCOTCH Graph structure pointed to
by grafptr with the source graph description available from stream stream
in the Scotch graph format (see section 5.1).
To ease the handling of source graph files by programs written in C as well as
in Fortran, the base value of the graph to read can be set to 0 or 1, by setting
the baseval parameter to the proper value. A value of -1 indicates that the
graph base should be the same as the one provided in the graph description
that is read from stream.
The flagval value is a combination of the following integer values, that may
be added or bitwise-ored:
0
Keep vertex and edge weights if they are present in the stream data.
1
Remove vertex weights. The graph read will have all of its vertex weights
set to one, regardless of what is specified in the stream data.
2
Remove edge weights. The graph read will have all of its edge weights
set to one, regardless of what is specified in the stream data.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the graph file.
Return values
SCOTCH graphLoad returns 0 if the graph structure has been successfully allocated and filled with the data read, and 1 else.
7.5.5
SCOTCH graphSave
Synopsis
71
int SCOTCH graphSave (const SCOTCH Graph *
FILE *
scotchfgraphsave (doubleprecision (*)
integer
integer
grafptr,
stream)
grafdat,
fildes,
ierr)
Description
The SCOTCH graphSave routine saves the contents of the SCOTCH Graph structure pointed to by grafptr to stream stream, in the Scotch graph format
(see section 5.1).
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the graph file.
Return values
SCOTCH graphSave returns 0 if the graph structure has been successfully written to stream, and 1 else.
7.5.6
SCOTCH graphBuild
Synopsis
int SCOTCH graphBuild (SCOTCH Graph
const SCOTCH
const SCOTCH
const SCOTCH
const SCOTCH
const SCOTCH
const SCOTCH
const SCOTCH
const SCOTCH
const SCOTCH
*
Num
Num
Num
Num
Num
Num
Num
Num
Num
scotchfgraphbuild (doubleprecision (*)
integer
integer
integer (*)
integer (*)
integer (*)
integer (*)
integer
integer (*)
integer (*)
integer
*
*
*
*
*
*
grafptr,
baseval,
vertnbr,
verttab,
vendtab,
velotab,
vlbltab,
edgenbr,
edgetab,
edlotab)
grafdat,
baseval,
vertnbr,
verttab,
vendtab,
velotab,
vlbltab,
edgenbr,
edgetab,
edlotab,
ierr)
Description
The SCOTCH graphBuild routine fills the source graph structure pointed to
by grafptr with all of the data that are passed to it.
72
baseval is the graph base value for index arrays (typically 0 for structures
built from C and 1 for structures built from Fortran). vertnbr is the number
of vertices. verttab is the adjacency index array, of size (vertnbr + 1) if
the edge array is compact (that is, if vendtab equals verttab + 1 or NULL),
or of size vertnbr else. vendtab is the adjacency end index array, of size
vertnbr if it is disjoint from verttab. velotab is the vertex load array, of
size vertnbr if it exists. vlbltab is the vertex label array, of size vertnbr if
it exists. edgenbr is the number of arcs (that is, twice the number of edges).
edgetab is the adjacency array, of size at least edgenbr (it can be more if the
edge array is not compact). edlotab is the arc load array, of size edgenbr if
it exists.
The vendtab, velotab, vlbltab and edlotab arrays are optional, and a NULL
pointer can be passed as argument whenever they are not defined. Since, in
Fortran, there is no null reference, passing the scotchfgraphbuild routine a
reference equal to verttab in the velotab or vlbltab fields makes them be
considered as missing arrays. The same holds for edlotab when it is passed a
reference equal to edgetab. Setting vendtab to refer to one cell after verttab
yields the same result, as it is the exact semantics of a compact vertex array.
To limit memory consumption, SCOTCH graphBuild does not copy array data,
but instead references them in the SCOTCH Graph structure. Therefore, great
care should be taken not to modify the contents of the arrays passed to
SCOTCH graphBuild as long as the graph structure is in use. Every update
of the arrays should be preceded by a call to SCOTCH graphFree, to free internal graph structures, and eventually followed by a new call to SCOTCH
graphBuild to re-build these internal structures so as to be able to use the
new graph.
To ensure that inconsistencies in user data do not result in an erroneous behavior of the libScotch routines, it is recommended, at least in the development
stage, to call the SCOTCH graphCheck routine on the newly created SCOTCH
Graph structure before calling any other libScotch routine.
Return values
SCOTCH graphBuild returns 0 if the graph structure has been successfully set
with all of the input data, and 1 else.
7.5.7
SCOTCH graphBase
Synopsis
int SCOTCH graphBase (SCOTCH Graph *
SCOTCH Num
scotchfgraphbase (doubleprecision (*)
integer
integer
Description
73
grafptr,
baseval)
grafdat,
baseval,
oldbaseval)
The SCOTCH graphBase routine sets the base of all graph indices according to
the given base value, and returns the old base value. This routine is a helper
for applications that do not handle base values properly.
In Fortan, the old base value is returned in the third parameter of the function
call.
Return values
SCOTCH graphBase returns the old base value.
7.5.8
SCOTCH graphCheck
Synopsis
int SCOTCH graphCheck (const SCOTCH Graph *
scotchfgraphcheck (doubleprecision (*)
integer
grafptr)
grafdat,
ierr)
Description
The SCOTCH graphCheck routine checks the consistency of the given SCOTCH
Graph structure. It can be used in client applications to determine if a graph
that has been created from used-generated data by means of the SCOTCH
graphBuild routine is consistent, prior to calling any other routines of the
libScotch library.
Return values
SCOTCH graphCheck returns 0 if graph data are consistent, and 1 else.
7.5.9
SCOTCH graphSize
Synopsis
void SCOTCH graphSize (const SCOTCH Graph *
SCOTCH Num *
SCOTCH Num *
scotchfgraphsize (doubleprecision (*)
integer
integer
grafptr,
vertptr,
edgeptr)
grafdat,
vertnbr,
edgenbr)
Description
The SCOTCH graphSize routine fills the two areas of type SCOTCH Num pointed
to by vertptr and edgeptr with the number of vertices and arcs (that is, twice
the number of edges) of the given graph pointed to by grafptr, respectively.
Any of these pointers can be set to NULL on input if the corresponding information is not needed. Else, the reference to a dummy area can be provided,
where all unwanted data will be written.
74
This routine is useful to get the size of a graph read by means of the SCOTCH
graphLoad routine, in order to allocate auxiliary arrays of proper sizes. If the
whole structure of the graph is wanted, function SCOTCH graphData should
be preferred.
7.5.10
SCOTCH graphData
Synopsis
void SCOTCH graphData (const SCOTCH Graph *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num **
SCOTCH Num **
SCOTCH Num **
SCOTCH Num **
SCOTCH Num *
SCOTCH Num **
SCOTCH Num **
scotchfgraphdata (doubleprecision (*)
integer (*)
integer
integer
integer
integer
integer
integer
integer
integer
integer
grafptr,
baseptr,
vertptr,
verttab,
vendtab,
velotab,
vlbltab,
edgeptr,
edgetab,
edlotab)
grafdat,
indxtab,
baseval,
vertnbr,
vertidx,
vendidx,
veloidx,
vlblidx,
edgenbr,
edgeidx,
edloidx)
Description
The SCOTCH graphData routine is the dual of the SCOTCH graphBuild routine.
It is a multiple accessor that returns scalar values and array references.
baseptr is the pointer to a location that will hold the graph base value for
index arrays (typically 0 for structures built from C and 1 for structures built
from Fortran). vertptr is the pointer to a location that will hold the number
of vertices. verttab is the pointer to a location that will hold the reference
to the adjacency index array, of size *vertptr + 1 if the adjacency array
is compact, or of size *vertptr else. vendtab is the pointer to a location
that will hold the reference to the adjacency end index array, and is equal to
verttab + 1 if the adjacency array is compact. velotab is the pointer to a
location that will hold the reference to the vertex load array, of size *vertptr.
vlbltab is the pointer to a location that will hold the reference to the vertex
label array, of size vertnbr. edgeptr is the pointer to a location that will
hold the number of arcs (that is, twice the number of edges). edgetab is the
pointer to a location that will hold the reference to the adjacency array, of
size at least *edgeptr. edlotab is the pointer to a location that will hold the
reference to the arc load array, of size *edgeptr.
75
Any of these pointers can be set to NULL on input if the corresponding information is not needed. Else, the reference to a dummy area can be provided,
where all unwanted data will be written.
Since there are no pointers in Fortran, a specific mechanism is used to allow
users to access graph arrays. The scotchfgraphdata routine is passed an
integer array, the first element of which is used as a base address from which all
other array indices are computed. Therefore, instead of returning references,
the routine returns integers, which represent the starting index of each of the
relevant arrays with respect to the base input array, or vertidx, the index
of verttab, if they do not exist. For instance, if some base array myarray
(1) is passed as parameter indxtab, then the first cell of array verttab
will be accessible as myarray(vertidx). In order for this feature to behave
properly, the indxtab array must be word-aligned with the graph arrays.
This is automatically enforced on most systems, but some care should be
taken on systems that allow one to access data that is not word-aligned. On
such systems, declaring the array after a dummy doubleprecision array can
coerce the compiler into enforcing the proper alignment.
7.5.11
SCOTCH graphStat
Synopsis
void SCOTCH graphStat (const SCOTCH Graph *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
double *
double *
SCOTCH Num *
SCOTCH Num *
double *
double *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
double *
double *
76
grafptr,
velominptr,
velomaxptr,
velosumptr,
veloavgptr,
velodltptr,
degrminptr,
degrmaxptr,
degravgptr,
degrdltptr,
edlominptr,
edlomaxptr,
edlosumptr,
edloavgptr,
edlodltptr)
scotchfgraphstat (doubleprecision (*)
integer
integer
integer
doubleprecision
doubleprecision
integer
integer
doubleprecision
doubleprecision
integer
integer
integer
doubleprecision
doubleprecision
grafdat,
velomin,
velomax,
velosum,
veloavg,
velodlt,
degrmin,
degrmax,
degravg,
degrdlt,
edlomin,
edlomax,
edlosum,
edloavg,
edlodlt)
Description
The SCOTCH graphStat routine produces some statistics regarding the graph
structure pointed to by grafptr. velomin, velomax, velosum, veloavg and
velodlt are the minimum vertex load, the maximum vertex load, the sum of
all vertex loads, the average vertex load, and the variance of the vertex loads,
respectively. degrmin, degrmax, degravg and degrdlt are the minimum vertex degree, the maximum vertex degree, the average vertex degree, and the
variance of the vertex degrees, respectively. edlomin, edlomax, edlosum,
edloavg and edlodlt are the minimum edge load, the maximum edge load,
the sum of all edge loads, the average edge load, and the variance of the edge
loads, respectively.
7.6
Graph mapping and partitioning routines
The first two routines provide high-level functionalities and free the user from the
burden of calling in sequence several of the low-level routines described afterward.
7.6.1
SCOTCH graphPart
Synopsis
int SCOTCH graphPart (const SCOTCH Graph *
const SCOTCH Num
const SCOTCH Strat *
SCOTCH Num *
scotchfgraphpart (doubleprecision (*)
integer
doubleprecision (*)
integer (*)
integer
Description
77
grafptr,
partnbr,
straptr,
parttab)
grafdat,
partnbr,
stradat,
parttab,
ierr)
The SCOTCH graphPart routine computes a partition into partnbr parts of the
source graph structure pointed to by grafptr, using the graph partitioning
strategy pointed to by stratptr, and returns the partition data in the array
pointed to by parttab.
The parttab array should have been previously allocated, of a size sufficient
to hold as many SCOTCH Num integers as there are vertices in the source graph.
On return, every array cell holds the number of the part to which the corresponding vertex is mapped. Parts are numbered from 0 to partnbr − 1.
Return values
SCOTCH graphPart returns 0 if the partition of the graph has been successfully
computed, and 1 else. In this latter case, the parttab array may however have
been partially or completely filled, but its content is not significant.
7.6.2
SCOTCH graphMap
Synopsis
int SCOTCH graphMap (const SCOTCH Graph *
const SCOTCH Arch *
const SCOTCH Strat *
SCOTCH Num *
scotchfgraphmap (doubleprecision (*)
doubleprecision (*)
doubleprecision (*)
integer (*)
integer
grafptr,
archptr,
straptr,
parttab)
grafdat,
archdat,
stradat,
parttab,
ierr)
Description
The SCOTCH graphMap routine computes a mapping of the source graph
structure pointed to by grafptr onto the target architecture pointed to by
archptr, using the mapping strategy pointed to by straptr, and returns the
mapping data in the array pointed to by parttab.
The parttab array should have been previously allocated, of a size sufficient
to hold as many SCOTCH Num integers as there are vertices in the source graph.
On return, every cell of the mapping array holds the number of the target
vertex to which the corresponding source vertex is mapped. The numbering
of target values is not based: target vertices are numbered from 0 to the
number of target vertices minus 1.
Return values
SCOTCH graphMap returns 0 if the partition of the graph has been successfully
computed, and 1 else. In this last case, the parttab array may however have
been partially or completely filled, but its content is not significant.
78
7.6.3
SCOTCH graphMapInit
Synopsis
int SCOTCH graphMapInit (const SCOTCH Graph *
SCOTCH Mapping *
const SCOTCH Arch *
SCOTCH Num *
scotchfgraphmapinit (doubleprecision (*)
doubleprecision (*)
doubleprecision (*)
integer (*)
integer
grafptr,
mappptr,
archptr,
parttab)
grafdat,
mappdat,
archdat,
parttab,
ierr)
Description
The SCOTCH graphMapInit routine fills the mapping structure pointed to by
mappptr with all of the data that is passed to it. Thus, all subsequent calls
to ordering routines such as SCOTCH graphMapCompute, using this mapping
structure as parameter, will place mapping results in field parttab.
parttab is the pointer to an array of as many SCOTCH Nums as there are vertices
in the graph pointed to by grafptr, and which will receive the indices of the
vertices of the target architecture pointed to by archptr.
It should be the first function to be called upon a SCOTCH Mapping structure.
When the mapping structure is no longer of use, call function SCOTCH graph
MapExit to free its internal structures.
Return values
SCOTCH graphMapInit returns 0 if the mapping structure has been successfully initialized, and 1 else.
7.6.4
SCOTCH graphMapExit
Synopsis
void SCOTCH graphMapExit (const SCOTCH Graph *
SCOTCH Mapping *
scotchfgraphmapexit (doubleprecision (*)
doubleprecision (*)
grafptr,
mappptr)
grafdat,
mappdat)
Description
The SCOTCH graphMapExit function frees the contents of a SCOTCH Mapping
structure previously initialized by SCOTCH graphMapInit. All subsequent calls
to SCOTCH graphMap* routines other than SCOTCH graphMapInit, using this
structure as parameter, may yield unpredictable results.
79
7.6.5
SCOTCH graphMapLoad
Synopsis
int SCOTCH graphMapLoad (const SCOTCH Graph *
SCOTCH Mapping *
FILE *
scotchfgraphmapload (doubleprecision (*)
doubleprecision (*)
integer
integer
grafptr,
mappptr,
stream)
grafdat,
mappdat,
fildes,
ierr)
Description
The SCOTCH graphMapLoad routine fills the SCOTCH Mapping structure pointed
to by mappptr with the mapping data available in the Scotch mapping format (see section 5.5) from stream stream.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the mapping file.
Return values
SCOTCH graphMapLoad returns 0 if the mapping structure has been successfully loaded from stream, and 1 else.
7.6.6
SCOTCH graphMapSave
Synopsis
int SCOTCH graphMapSave (const SCOTCH Graph *
const SCOTCH Mapping *
FILE *
scotchfgraphmapsave (doubleprecision (*)
doubleprecision (*)
integer
integer
grafptr,
mappptr,
stream)
grafdat,
mappdat,
fildes,
ierr)
Description
The SCOTCH graphMapSave routine saves the contents of the SCOTCH Mapping
structure pointed to by mappptr to stream stream, in the Scotch mapping
format (see section 5.5).
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the mapping file.
Return values
SCOTCH graphMapSave returns 0 if the mapping structure has been successfully written to stream, and 1 else.
80
7.6.7
SCOTCH graphMapCompute
Synopsis
int SCOTCH graphMapCompute (const SCOTCH Graph *
SCOTCH Mapping *
const SCOTCH Strat *
scotchfgraphmapcompute (doubleprecision (*)
doubleprecision (*)
doubleprecision (*)
integer
grafptr,
mappptr,
straptr)
grafdat,
mappdat,
stradat,
ierr)
Description
The SCOTCH graphMapCompute routine computes a mapping on the given
SCOTCH Mapping structure pointed to by mappptr using the mapping strategy
pointed to by stratptr.
On return, every cell of the mapping array (see section 7.6.3) holds the number
of the target vertex to which the corresponding source vertex is mapped. The
numbering of target values is not based: target vertices are numbered from 0
to the number of target vertices, minus 1.
Return values
SCOTCH graphMapCompute returns 0 if the mapping has been successfully computed, and 1 else. In this latter case, the mapping array may however have
been partially or completely filled, but its content is not significant.
7.6.8
SCOTCH graphMapView
Synopsis
int SCOTCH graphMapView (const SCOTCH Graph *
const SCOTCH Mapping *
FILE *
scotchfgraphmapview (doubleprecision (*)
doubleprecision (*)
integer
integer
grafptr,
mappptr,
stream)
grafdat,
mappdat,
fildes,
ierr)
Description
The SCOTCH mapView routine summarizes statistical information on the mapping pointed to by mappptr (load of target processors, number of neighboring
domains, average dilation and expansion, edge cut size, distribution of edge
dilations), and prints these results to stream stream.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the output data file.
81
Return values
SCOTCH mapView returns 0 if the data has been successfully written to stream,
and 1 else.
7.7
Graph ordering routines
The first routine provides high-level functionality and frees the user from the burden
of calling in sequence several of the low-level routines described afterward.
7.7.1
SCOTCH graphOrder
Synopsis
int SCOTCH graphOrder (const SCOTCH Graph *
const SCOTCH Strat *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
scotchfgraphorder (doubleprecision (*)
doubleprecision (*)
integer (*)
integer (*)
integer
integer (*)
integer (*)
integer
grafptr,
straptr,
permtab,
peritab,
cblkptr,
rangtab,
treetab)
grafdat,
stradat,
permtab,
peritab,
cblknbr,
rangtab,
treetab,
ierr)
Description
The SCOTCH graphOrder routine computes a block ordering of the unknowns
of the symmetric sparse matrix the adjacency structure of which is represented
by the source graph structure pointed to by grafptr, using the ordering
strategy pointed to by stratptr, and returns ordering data in the scalar
pointed to by cblkptr and the four arrays permtab, peritab, rangtab and
treetab.
The permtab, peritab, rangtab and treetab arrays should have been previously allocated, of a size sufficient to hold as many SCOTCH Num integers as
there are vertices in the source graph, plus one in the case of rangtab. Any
of the five output fields can be set to NULL if the corresponding information is
not needed. Since, in Fortran, there is no null reference, passing a reference
to grafptr in these fields will have the same effect.
On return, permtab holds the direct permutation of the unknowns, that is,
vertex i of the original graph has index permtab[i] in the reordered graph,
while peritab holds the inverse permutation, that is, vertex i in the reordered
graph had index peritab[i] in the original graph. All of these indices are
numbered according to the base value of the source graph: permutation indices
are numbered from baseval to vertnbr + baseval − 1, that is, from 0 to
82
vertnbr − 1 if the graph base is 0, and from 1 to vertnbr if the graph base
is 1.
The three other result fields, *cblkptr, rangtab and treetab, contain data
related to the block structure. *cblkptr holds the number of column blocks
of the produced ordering, and rangtab holds the starting indices of each of the
permuted column blocks, in increasing order, so that column block i starts at
index rangtab[i] and ends at index (rangtab[i+1]−1), inclusive, in the new
ordering. treetab holds the separators tree structure, that is, treetab[i] is
the index of the father of column block i in the separators tree, or −1 if column
block i is the root of the separators tree. Please refer to Section 7.2.5 for more
information.
Return values
SCOTCH graphOrder returns 0 if the ordering of the graph has been successfully
computed, and 1 else. In this last case, the rangtab, permtab, and peritab
arrays may however have been partially or completely filled, but their contents
are not significant.
7.7.2
SCOTCH graphOrderInit
Synopsis
int SCOTCH graphOrderInit (const SCOTCH Graph *
SCOTCH Ordering *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
scotchfgraphorderinit (doubleprecision (*)
doubleprecision (*)
integer (*)
integer (*)
integer
integer (*)
integer (*)
integer
grafptr,
ordeptr,
permtab,
peritab,
cblkptr,
rangtab,
treetab)
grafdat,
ordedat,
permtab,
peritab,
cblknbr,
rangtab,
treetab,
ierr)
Description
The SCOTCH graphOrderInit routine fills the ordering structure pointed to by
ordeptr with all of the data that are passed to it. Thus, all subsequent calls
to ordering routines such as SCOTCH graphOrderCompute, using this ordering
structure as parameter, will place ordering results in fields permtab, peritab,
*cblkptr, rangtab or treetab, if they are not set to NULL.
permtab is the ordering permutation array, of size vertnbr, peritab is the
inverse ordering permutation array, of size vertnbr, cblkptr is the pointer
to a SCOTCH Num that will receive the number of produced column blocks,
rangtab is the array that holds the column block span information, of size
83
vertnbr + 1, and treetab is the array holding the structure of the separators
tree, of size vertnbr. See the above manual page of SCOTCH graphOrder, as
well as section 7.2.5, for an explanation of the semantics of all of these fields.
The SCOTCH graphOrderInit routine should be the first function to be called
upon a SCOTCH Ordering structure for ordering graphs. When the ordering
structure is no longer of use, the SCOTCH graphOrderExit function must be
called, in order to to free its internal structures.
Return values
SCOTCH graphOrderInit returns 0 if the ordering structure has been successfully initialized, and 1 else.
7.7.3
SCOTCH graphOrderExit
Synopsis
void SCOTCH graphOrderExit (const SCOTCH Graph *
SCOTCH Ordering *
scotchfgraphorderexit (doubleprecision (*)
doubleprecision (*)
grafptr,
ordeptr)
grafdat,
ordedat)
Description
The SCOTCH graphOrderExit function frees the contents of a SCOTCH
Ordering structure previously initialized by SCOTCH graphOrderInit. All
subsequent calls to SCOTCH graphOrder* routines other than SCOTCH graph
OrderInit, using this structure as parameter, may yield unpredictable results.
7.7.4
SCOTCH graphOrderLoad
Synopsis
int SCOTCH graphOrderLoad (const SCOTCH Graph *
SCOTCH Ordering *
FILE *
scotchfgraphorderload (doubleprecision (*)
doubleprecision (*)
integer
integer
grafptr,
ordeptr,
stream)
grafdat,
ordedat,
fildes,
ierr)
Description
The SCOTCH graphOrderLoad routine fills the SCOTCH Ordering structure
pointed to by ordeptr with the ordering data available in the Scotch ordering format (see section 5.6) from stream stream.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the ordering file.
84
Return values
SCOTCH graphOrderLoad returns 0 if the ordering structure has been successfully loaded from stream, and 1 else.
7.7.5
SCOTCH graphOrderSave
Synopsis
int SCOTCH graphOrderSave (const SCOTCH Graph *
const SCOTCH Ordering *
FILE *
scotchfgraphordersave (doubleprecision (*)
doubleprecision (*)
integer
integer
grafptr,
ordeptr,
stream)
grafdat,
ordedat,
fildes,
ierr)
Description
The SCOTCH graphOrderSave routine saves the contents of the SCOTCH
Ordering structure pointed to by ordeptr to stream stream, in the Scotch
ordering format (see section 5.6).
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the ordering file.
Return values
SCOTCH graphOrderSave returns 0 if the ordering structure has been successfully written to stream, and 1 else.
7.7.6
SCOTCH graphOrderSaveMap
Synopsis
int SCOTCH graphOrderSaveMap (const SCOTCH Graph *
const SCOTCH Ordering *
FILE *
scotchfgraphordersavemap (doubleprecision (*)
doubleprecision (*)
integer
integer
grafptr,
ordeptr,
stream)
grafdat,
ordedat,
fildes,
ierr)
Description
The SCOTCH graphOrderSaveMap routine saves the block partitioning data associated with the SCOTCH Ordering structure pointed to by ordeptr to stream
stream, in the Scotch mapping format (see section 5.5). A target domain
number is associated with every block, such that all node vertices belonging
to the same block are shown as belonging to the same target vertex. The
85
resulting mapping file can be used by the gout program (see Section 6.3.12)
to produce pictures showing the different separators and blocks.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the mapping file.
Return values
SCOTCH graphOrderSaveMap returns 0 if the ordering structure has been successfully written to stream, and 1 else.
7.7.7
SCOTCH graphOrderSaveTree
Synopsis
int SCOTCH graphOrderSaveTree (const SCOTCH Graph *
const SCOTCH Ordering *
FILE *
scotchfgraphordersavetree (doubleprecision (*)
doubleprecision (*)
integer
integer
grafptr,
ordeptr,
stream)
grafdat,
ordedat,
fildes,
ierr)
Description
The SCOTCH graphOrderSaveTree routine saves the tree hierarchy information associated with the SCOTCH Ordering structure pointed to by ordeptr
to stream stream.
The format of the tree output file resembles the one of a mapping or ordering
file: it is made up of as many lines as there are vertices in the ordering. Each
of these lines holds two integer numbers. The first one is the index or the
label of the vertex, and the second one is the index of its parent node in the
separators tree, or −1 if the vertex belongs to a root node.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the tree mapping file.
Return values
SCOTCH graphOrderSaveTree returns 0 if the separators tree structure has
been successfully written to stream, and 1 else.
7.7.8
SCOTCH graphOrderCheck
Synopsis
int SCOTCH graphOrderCheck (const SCOTCH Graph *
const SCOTCH Ordering *
scotchfgraphordercheck (doubleprecision (*)
doubleprecision (*)
integer
86
grafptr,
ordeptr)
grafdat,
ordedat,
ierr)
Description
The SCOTCH graphOrderCheck routine checks the consistency of the given
SCOTCH Ordering structure pointed to by ordeptr.
Return values
SCOTCH graphOrderCheck returns 0 if ordering data are consistent, and 1 else.
7.7.9
SCOTCH graphOrderCompute
Synopsis
int SCOTCH graphOrderCompute (const SCOTCH Graph *
SCOTCH Ordering *
const SCOTCH Strat *
scotchfgraphordercompute (doubleprecision (*)
doubleprecision (*)
doubleprecision (*)
integer
grafptr,
ordeptr,
straptr)
grafdat,
ordedat,
stradat,
ierr)
Description
The SCOTCH graphOrderCompute routine computes a block ordering of the
graph structure pointed to by grafptr, using the ordering strategy pointed
to by stratptr, and stores its result in the ordering structure pointed to by
ordeptr.
On return, the ordering structure holds a block ordering of the given graph
(see section 7.7.2 for a description of the ordering fields).
Return values
SCOTCH graphOrderCompute returns 0 if the ordering has been successfully
computed, and 1 else. In this latter case, the ordering arrays may however
have been partially or completely filled, but their contents are not significant.
7.7.10
SCOTCH graphOrderComputeList
Synopsis
int SCOTCH graphOrderComputeList (const SCOTCH Graph *
SCOTCH Ordering *
SCOTCH Num
SCOTCH Num *
const SCOTCH Strat *
scotchfgraphordercompute (doubleprecision (*)
doubleprecision (*)
integer
integer (*)
doubleprecision (*)
integer
87
grafdat,
ordedat,
listnbr,
listtab,
stradat,
ierr)
grafptr,
ordeptr,
listnbr,
listtab,
straptr)
Description
The SCOTCH graphOrderComputeList routine computes a block ordering of a
subgraph of the graph structure pointed to by grafptr, using the ordering
strategy pointed to by stratptr, and stores its result in the ordering structure
pointed to by ordeptr. The induced subgraph is described by means of a
vertex list: listnbr holds the number of vertices to keep in the induced
subgraph, the indices of which are given, in any order, in the listtab array.
On return, the ordering structure holds a block ordering of the induced subgraph (see section 7.2.5 for a description of the ordering fields). To compute this ordering, graph ordering methods such as the minimum degree and
minimum fill methods will base on the original degree of the induced graph
vertices, their non-induced neighbors being considered as halo vertices (see
Section 3.2.3 for more information on halo vertices).
Because an ordering always refers to the full graph, the ordering computed by SCOTCH graphOrderComputeList is divided into two distinct parts:
the induced graph vertices are ordered by applying to the induced graph
the strategy provided by the stratptr parameter, while non-induced vertex are ordered consecutively with the highest available indices. Consequently, the permuted indices of induced vertices range from baseval to
(listnbr + baseval − 1), while the permuted indices of the remaining vertices range from (listnbr + baseval) to (vertnbr + baseval − 1), inclusive.
The separation tree yielded by SCOTCH graphOrderComputeList reflects this
property: it is made of two branches, the first one corresponding to the induced subgraph, and the second one to the remaining vertices. Since these
two subgraphs are not considered to be connected, both will have their own
root, represented by a −1 value in the treetab array of the ordering.
Return values
SCOTCH graphOrderComputeList returns 0 if the ordering has been successfully computed, and 1 else. In this latter case, the ordering arrays may however
have been partially or completely filled, but their contents are not significant.
7.8
7.8.1
Mesh handling routines
SCOTCH meshInit
Synopsis
int SCOTCH meshInit (SCOTCH Mesh *
meshptr)
scotchfmeshinit (doubleprecision (*)
integer
meshdat,
ierr)
Description
The SCOTCH meshInit function initializes a SCOTCH Mesh structure so as to
make it suitable for future operations. It should be the first function to be
called upon a SCOTCH Mesh structure. When the mesh data is no longer of
use, call function SCOTCH meshExit to free its internal structures.
88
Return values
SCOTCH meshInit returns 0 if the mesh structure has been successfully initialized, and 1 else.
7.8.2
SCOTCH meshExit
Synopsis
void SCOTCH meshExit (SCOTCH Mesh *
meshptr)
scotchfmeshexit (doubleprecision (*)
meshdat)
Description
The SCOTCH meshExit function frees the contents of a SCOTCH Mesh structure
previously initialized by SCOTCH meshInit. All subsequent calls to SCOTCH
mesh* routines other than SCOTCH meshInit, using this structure as parameter, may yield unpredictable results.
7.8.3
SCOTCH meshLoad
Synopsis
int SCOTCH meshLoad (SCOTCH Mesh *
FILE *
SCOTCH Num
meshptr,
stream,
baseval)
scotchfmeshload (doubleprecision (*)
integer
integer
integer
meshdat,
fildes,
baseval,
ierr)
Description
The SCOTCH meshLoad routine fills the SCOTCH Mesh structure pointed to by
meshptr with the source mesh description available from stream stream in
the Scotch mesh format (see section 5.2).
To ease the handling of source mesh files by programs written in C as well as
in Fortran, The base value of the mesh to read can be set to 0 or 1, by setting
the baseval parameter to the proper value. A value of -1 indicates that the
mesh base should be the same as the one provided in the mesh description
that is read from stream.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the mesh file.
Return values
SCOTCH meshLoad returns 0 if the mesh structure has been successfully allocated and filled with the data read, and 1 else.
89
7.8.4
SCOTCH meshSave
Synopsis
int SCOTCH meshSave (const SCOTCH Mesh *
FILE *
scotchfmeshsave (doubleprecision (*)
integer
integer
meshptr,
stream)
meshdat,
fildes,
ierr)
Description
The SCOTCH meshSave routine saves the contents of the SCOTCH Mesh structure
pointed to by meshptr to stream stream, in the Scotch mesh format (see
section 5.2).
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the mesh file.
Return values
SCOTCH meshSave returns 0 if the mesh structure has been successfully written
to stream, and 1 else.
7.8.5
SCOTCH meshBuild
Synopsis
int SCOTCH meshBuild (SCOTCH Mesh *
const SCOTCH Num
const SCOTCH Num
const SCOTCH Num
const SCOTCH Num
const SCOTCH Num
const SCOTCH Num
const SCOTCH Num
const SCOTCH Num
const SCOTCH Num
const SCOTCH Num
const SCOTCH Num
90
*
*
*
*
*
*
meshptr,
velmbas,
vnodbas,
velmnbr,
vnodnbr,
verttab,
vendtab,
velotab,
vnlotab,
vlbltab,
edgenbr,
edgetab)
scotchfmeshbuild (doubleprecision (*)
integer
integer
integer
integer
integer (*)
integer (*)
integer (*)
integer (*)
integer (*)
integer
integer (*)
integer
meshdat,
velmbas,
vnodbas,
velmnbr,
vnodnbr,
verttab,
vendtab,
velotab,
vnlotab,
vlbltab,
edgenbr,
edgetab,
ierr)
Description
The SCOTCH meshBuild routine fills the source mesh structure pointed to by
meshptr with all of the data that is passed to it.
velmbas and vnodbas are the base values for the element and node vertices, respectively. velmnbr and vnodnbr are the number of element and
node vertices, respectively, such that either velmbas + velmnbr = vnodnbr or
vnodbas+ vnodnbr = velmnbr holds, and typically min(velmbas, vnodbas) is
0 for structures built from C and 1 for structures built from Fortran. verttab
is the adjacency index array, of size (velmnbr + vnodnbr + 1) if the edge array is compact (that is, if vendtab equals vendtab + 1 or NULL), or of size
(velmnbr + vnodnbr1) else. vendtab is the adjacency end index array, of size
(velmnbr + vnodnbr) if it is disjoint from verttab. velotab is the element
vertex load array, of size velmnbr if it exists. vnlotab is the node vertex load
array, of size vnodnbr if it exists. vlbltab is the vertex label array, of size
(velmnbr+ vnodnbr) if it exists. edgenbr is the number of arcs (that is, twice
the number of edges). edgetab is the adjacency array, of size at least edgenbr
(it can be more if the edge array is not compact).
The vendtab, velotab, vnlotab and vlbltab arrays are optional, and a NULL
pointer can be passed as argument whenever they are not defined. Since, in
Fortran, there is no null reference, passing the scotchfmeshbuild routine a
reference equal to verttab in the velotab, vnlotab or vlbltab fields makes
them be considered as missing arrays. Setting vendtab to refer to one cell
after verttab yields the same result, as it is the exact semantics of a compact
vertex array.
To limit memory consumption, SCOTCH meshBuild does not copy array data,
but instead references them in the SCOTCH Mesh structure. Therefore, great
care should be taken not to modify the contents of the arrays passed to
SCOTCH meshBuild as long as the mesh structure is in use. Every update
of the arrays should be preceded by a call to SCOTCH meshExit, to free internal mesh structures, and eventually followed by a new call to SCOTCH
meshBuild to re-build these internal structures so as to be able to use the
new mesh.
To ensure that inconsistencies in user data do not result in an erroneous behavior of the libScotch routines, it is recommended, at least in the development
91
stage, to call the SCOTCH meshCheck routine on the newly created SCOTCH
Mesh structure, prior to any other calls to libScotch routines.
Return values
SCOTCH meshBuild returns 0 if the mesh structure has been successfully set
with all of the input data, and 1 else.
7.8.6
SCOTCH meshCheck
Synopsis
int SCOTCH meshCheck (const SCOTCH Mesh *
scotchfmeshcheck (doubleprecision (*)
integer
meshptr)
meshdat,
ierr)
Description
The SCOTCH meshCheck routine checks the consistency of the given SCOTCH
Mesh structure. It can be used in client applications to determine if a mesh
that has been created from used-generated data by means of the SCOTCH
meshBuild routine is consistent, prior to calling any other routines of the
libScotch library.
Return values
SCOTCH meshCheck returns 0 if mesh data are consistent, and 1 else.
7.8.7
SCOTCH meshSize
Synopsis
void SCOTCH meshSize (const SCOTCH Mesh *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
scotchfmeshsize (doubleprecision (*)
integer
integer
integer
meshptr,
velmptr,
vnodptr,
edgeptr)
meshdat,
velmnbr,
vnodnbr,
edgenbr)
Description
The SCOTCH meshSize routine fills the three areas of type SCOTCH Num pointed
to by velmptr, vnodptr and edgeptr with the number of element vertices,
node vertices and arcs (that is, twice the number of edges) of the given mesh
pointed to by meshptr, respectively.
Any of these pointers can be set to NULL on input if the corresponding information is not needed. Else, the reference to a dummy area can be provided,
where all unwanted data will be written.
92
This routine is useful to get the size of a mesh read by means of the SCOTCH
meshLoad routine, in order to allocate auxiliary arrays of proper sizes. If the
whole structure of the mesh is wanted, function SCOTCH meshData should be
preferred.
7.8.8
SCOTCH meshData
Synopsis
void SCOTCH meshData (const SCOTCH Mesh *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num **
SCOTCH Num **
SCOTCH Num **
SCOTCH Num **
SCOTCH Num **
SCOTCH Num *
SCOTCH Num **
SCOTCH Num *
scotchfmeshdata (doubleprecision (*)
integer (*)
integer
integer
integer
integer
integer
integer
integer
integer
integer
integer
integer
integer
meshptr,
vebaptr,
vnbaptr,
velmptr,
vnodptr,
verttab,
vendtab,
velotab,
vnlotab,
vlbltab,
edgeptr,
edgetab,
degrptr)
meshdat,
indxtab,
velobas,
vnlobas,
velmnbr,
vnodnbr,
vertidx,
vendidx,
veloidx,
vnloidx,
vlblidx,
edgenbr,
edgeidx,
degrmax)
Description
The SCOTCH meshData routine is the dual of the SCOTCH meshBuild routine.
It is a multiple accessor that returns scalar values and array references.
vebaptr and vnbaptr are pointers to locations that will hold the mesh base
value for elements and nodes, respectively (the minimum of these two values is typically 0 for structures built from C and 1 for structures built from
Fortran). velmptr and vnodptr are pointers to locations that will hold the
number of element and node vertices, respectively. verttab is the pointer
to a location that will hold the reference to the adjacency index array, of
size (*velmptr + *vnodptr + 1) if the adjacency array is compact, or of size
(*velmptr+*vnodptr) else. vendtab is the pointer to a location that will hold
93
the reference to the adjacency end index array, and is equal to verttab + 1
if the adjacency array is compact. velotab and vnlotab are pointers to
locations that will hold the reference to the element and node vertex load
arrays, of sizes *velmptr and *vnodptr, respectively. vlbltab is the pointer
to a location that will hold the reference to the vertex label array, of size
(*velmptr + *vnodptr). edgeptr is the pointer to a location that will hold
the number of arcs (that is, twice the number of edges). edgetab is the pointer
to a location that will hold the reference to the adjacency array, of size at least
edgenbr. degrptr is the pointer to a location that will hold the maximum
vertex degree computed across all element and node vertices.
Any of these pointers can be set to NULL on input if the corresponding information is not needed. Else, the reference to a dummy area can be provided,
where all unwanted data will be written.
Since there are no pointers in Fortran, a specific mechanism is used to allow
users to access mesh arrays. The scotchfmeshdata routine is passed an integer array, the first element of which is used as a base address from which all
other array indices are computed. Therefore, instead of returning references,
the routine returns integers, which represent the starting index of each of the
relevant arrays with respect to the base input array, or vertidx, the index
of verttab, if they do not exist. For instance, if some base array myarray
(1) is passed as parameter indxtab, then the first cell of array verttab will
be accessible as myarray(vertidx). In order for this feature to behave properly, the indxtab array must be word-aligned with the mesh arrays. This is
automatically enforced on most systems, but some care should be taken on
systems that allow one to access data that is not word-aligned. On such systems, declaring the array after a dummy doubleprecision array can coerce
the compiler into enforcing the proper alignment.
7.8.9
SCOTCH meshStat
Synopsis
void SCOTCH meshStat (const SCOTCH Mesh *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
double *
double *
SCOTCH Num *
SCOTCH Num *
double *
double *
SCOTCH Num *
SCOTCH Num *
double *
double *
94
meshptr,
vnlominptr,
vnlomaxptr,
vnlosumptr,
vnloavgptr,
vnlodltptr,
edegminptr,
edegmaxptr,
edegavgptr,
edegdltptr,
ndegminptr,
ndegmaxptr,
ndegavgptr,
ndegdltptr)
scotchfmeshstat (doubleprecision (*)
integer
integer
integer
doubleprecision
doubleprecision
integer
integer
doubleprecision
doubleprecision
integer
integer
doubleprecision
doubleprecision
meshdat,
vnlomin,
vnlomax,
vnlosum,
vnloavg,
vnlodlt,
edegmin,
edegmax,
edegavg,
edegdlt,
ndegmin,
ndegmax,
ndegavg,
ndegdlt)
Description
The SCOTCH meshStat routine produces some statistics regarding the mesh
structure pointed to by meshptr. vnlomin, vnlomax, vnlosum, vnloavg and
vnlodlt are the minimum node vertex load, the maximum node vertex load,
the sum of all node vertex loads, the average node vertex load, and the variance of the node vertex loads, respectively. edegmin, edegmax, edegavg and
edegdlt are the minimum element vertex degree, the maximum element vertex degree, the average element vertex degree, and the variance of the element
vertex degrees, respectively. ndegmin, ndegmax, ndegavg and ndegdlt are the
minimum element vertex degree, the maximum element vertex degree, the average element vertex degree, and the variance of the element vertex degrees,
respectively.
7.8.10
SCOTCH meshGraph
Synopsis
int SCOTCH meshGraph (const SCOTCH Mesh *
SCOTCH Graph *
scotchfmeshgraph (doubleprecision (*)
doubleprecision (*)
integer
meshptr,
grafptr)
meshdat,
grafdat,
ierr)
Description
The SCOTCH meshGraph routine builds a graph from a mesh. It creates in the
SCOTCH Graph structure pointed to by grafptr a graph having as many vertices as there are nodes in the SCOTCH Mesh structure pointed to by meshptr,
and where there is an edge between any two graph vertices if and only if
there exists in the mesh an element containing both of the associated nodes.
Consequently, all of the elements of the mesh are turned into cliques in the
resulting graph.
95
In order to save memory space as well as computation time, in the current
implementation of SCOTCH meshGraph, some mesh arrays are shared with the
graph structure. Therefore, one should make sure that the graph must no
longer be used after the mesh structure is freed. The graph structure can be
freed before or after the mesh structure, but must not be used after the mesh
structure is freed.
Return values
SCOTCH meshGraph returns 0 if the graph structure has been successfully allocated and filled, and 1 else.
7.9
Mesh ordering routines
The first routine provides high-level functionality and frees the user from the burden
of calling in sequence several of the low-level routines described afterward.
7.9.1
SCOTCH meshOrder
Synopsis
int SCOTCH meshOrder (const SCOTCH Mesh *
const SCOTCH Strat *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
scotchfmeshorder (doubleprecision (*)
doubleprecision (*)
integer (*)
integer (*)
integer
integer (*)
integer (*)
integer
meshptr,
straptr,
permtab,
peritab,
cblkptr,
rangtab,
treetab)
meshdat,
stradat,
permtab,
peritab,
cblknbr,
rangtab,
treetab,
ierr)
Description
The SCOTCH meshOrder routine computes a block ordering of the unknowns of
the symmetric sparse matrix the adjacency structure of which is represented
by the elements that connect the nodes of the source mesh structure pointed to
by meshptr, using the ordering strategy pointed to by stratptr, and returns
ordering data in the scalar pointed to by cblkptr and the four arrays permtab,
peritab, rangtab and treetab.
The permtab, peritab, rangtab and treetab arrays should have been previously allocated, of a size sufficient to hold as many SCOTCH Num integers as
there are node vertices in the source mesh, plus one in the case of rangtab.
Any of the five output fields can be set to NULL if the corresponding information is not needed. Since, in Fortran, there is no null reference, passing a
reference to meshptr in these fields will have the same effect.
96
On return, permtab holds the direct permutation of the unknowns, that is,
node vertex i of the original mesh has index permtab[i] in the reordered
mesh, while peritab holds the inverse permutation, that is, node vertex i
in the reordered mesh had index peritab[i] in the original mesh. All of
these indices are numbered according to the base value of the source mesh:
permutation indices are numbered from min(velmbas, vnodbas) to vnodnbr+
min(velmbas, vnodbas) − 1, that is, from 0 to vnodnbr − 1 if the mesh base
is 0, and from 1 to vnodnbr if the mesh base is 1. The base value for mesh
orderings is taken as min(velmbas, vnodbas), and not just as vnodbas, such
that orderings that are computed on some mesh have exactly the same index
range as orderings that would be computed on the graph obtained from the
original mesh by means of the SCOTCH meshGraph routine.
The three other result fields, *cblkptr, rangtab and treetab, contain data
related to the block structure. *cblkptr holds the number of column blocks
of the produced ordering, and rangtab holds the starting indices of each of the
permuted column blocks, in increasing order, so that column block i starts at
index rangtab[i] and ends at index (rangtab[i+1]−1), inclusive, in the new
ordering. treetab holds the separators tree structure, that is, treetab[i] is
the index of the father of column block i in the separators tree, or −1 if column
block i is the root of the separators tree. Please refer to Section 7.2.5 for more
information.
Return values
SCOTCH meshOrder returns 0 if the ordering of the mesh has been successfully
computed, and 1 else. In this last case, the rangtab, permtab, and peritab
arrays may however have been partially or completely filled, but their contents
are not significant.
7.9.2
SCOTCH meshOrderInit
Synopsis
int SCOTCH meshOrderInit (const SCOTCH Mesh *
SCOTCH Ordering *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
SCOTCH Num *
scotchfmeshorderinit (doubleprecision (*)
doubleprecision (*)
integer (*)
integer (*)
integer
integer (*)
integer (*)
integer
Description
97
meshptr,
ordeptr,
permtab,
peritab,
cblkptr,
rangtab,
treetab)
meshdat,
ordedat,
permtab,
peritab,
cblknbr,
rangtab,
treetab,
ierr)
The SCOTCH meshOrderInit routine fills the ordering structure pointed to by
ordeptr with all of the data that are passed to it. Thus, all subsequent calls
to ordering routines such as SCOTCH meshOrderCompute, using this ordering
structure as parameter, will place ordering results in fields permtab, peritab,
*cblkptr, rangtab or treetab, if they are not set to NULL.
permtab is the ordering permutation array, of size vnodnbr, peritab is the
inverse ordering permutation array, of size vnodnbr, cblkptr is the pointer
to a SCOTCH Num that will receive the number of produced column blocks,
rangtab is the array that holds the column block span information, of size
vnodnbr + 1, and treetab is the array holding the structure of the separators
tree, of size vnodnbr. See the above manual page of SCOTCH meshOrder, as
well as section 7.2.5, for an explanation of the semantics of all of these fields.
The SCOTCH meshOrderInit routine should be the first function to be called
upon a SCOTCH Ordering structure for ordering meshes. When the ordering
structure is no longer of use, the SCOTCH meshOrderExit function must be
called, in order to to free its internal structures.
Return values
SCOTCH meshOrderInit returns 0 if the ordering structure has been successfully initialized, and 1 else.
7.9.3
SCOTCH meshOrderExit
Synopsis
void SCOTCH meshOrderExit (const SCOTCH Mesh *
SCOTCH Ordering *
scotchfmeshorderexit (doubleprecision (*)
doubleprecision (*)
meshptr,
ordeptr)
meshdat,
ordedat)
Description
The SCOTCH meshOrderExit function frees the contents of a SCOTCH Ordering
structure previously initialized by SCOTCH meshOrderInit. All subsequent
calls to SCOTCH meshOrder* routines other than SCOTCH meshOrderInit, using this structure as parameter, may yield unpredictable results.
7.9.4
SCOTCH meshOrderSave
Synopsis
int SCOTCH meshOrderSave (const SCOTCH Mesh *
const SCOTCH Ordering *
FILE *
scotchfmeshordersave (doubleprecision (*)
doubleprecision (*)
integer
integer
98
meshptr,
ordeptr,
stream)
meshdat,
ordedat,
fildes,
ierr)
Description
The SCOTCH meshOrderSave routine saves the contents of the SCOTCH
Ordering structure pointed to by ordeptr to stream stream, in the Scotch
ordering format (see section 5.6).
Return values
SCOTCH meshOrderSave returns 0 if the ordering structure has been successfully written to stream, and 1 else.
7.9.5
SCOTCH meshOrderSaveMap
Synopsis
int SCOTCH meshOrderSaveMap (const SCOTCH Mesh *
const SCOTCH Ordering *
FILE *
scotchfmeshordersavemap (doubleprecision (*)
doubleprecision (*)
integer
integer
meshptr,
ordeptr,
stream)
meshdat,
ordedat,
fildes,
ierr)
Description
The SCOTCH meshOrderSaveMap routine saves the block partitioning data associated with the SCOTCH Ordering structure pointed to by ordeptr to stream
stream, in the Scotch mapping format (see section 5.5). A target domain
number is associated with every block, such that all node vertices belonging
to the same block are shown as belonging to the same target vertex.
This mapping file can then be used by the gout program (see section 6.3.12)
to produce pictures showing the different separators and blocks. Since gout
only takes graphs as input, the mesh has to be converted into a graph by
means of the gmk msh program (see section 6.3.8).
Return values
SCOTCH meshOrderSaveMap returns 0 if the ordering structure has been successfully written to stream, and 1 else.
7.9.6
SCOTCH meshOrderSaveTree
Synopsis
int SCOTCH meshOrderSaveTree (const SCOTCH Mesh *
const SCOTCH Ordering *
FILE *
scotchfmeshordersavetree (doubleprecision (*)
doubleprecision (*)
integer
integer
99
meshptr,
ordeptr,
stream)
meshdat,
ordedat,
fildes,
ierr)
Description
The SCOTCH meshOrderSaveTree routine saves the tree hierarchy information
associated with the SCOTCH Ordering structure pointed to by ordeptr to
stream stream.
The format of the tree output file resembles the one of a mapping or ordering
file: it is made up of as many lines as there are node vertices in the ordering.
Each of these lines holds two integer numbers. The first one is the index or
the label of the node vertex, starting from baseval, and the second one is the
index of its parent node in the separators tree, or −1 if the vertex belongs to
a root node.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the tree mapping file.
Return values
SCOTCH meshOrderSaveTree returns 0 if the separators tree structure has been
successfully written to stream, and 1 else.
7.9.7
SCOTCH meshOrderCheck
Synopsis
int SCOTCH meshOrderCheck (const SCOTCH Mesh *
const SCOTCH Ordering *
scotchfmeshordercheck (doubleprecision (*)
doubleprecision (*)
integer
meshptr,
ordeptr)
meshdat,
ordedat,
ierr)
Description
The SCOTCH meshOrderCheck routine checks the consistency of the given
SCOTCH Ordering structure pointed to by ordeptr.
Return values
SCOTCH meshOrderCheck returns 0 if ordering data are consistent, and 1 else.
7.9.8
SCOTCH meshOrderCompute
Synopsis
int SCOTCH meshOrderCompute (const SCOTCH Mesh *
SCOTCH Ordering *
const SCOTCH Strat *
scotchfmeshordercompute (doubleprecision (*)
doubleprecision (*)
doubleprecision (*)
integer
100
meshptr,
ordeptr,
straptr)
meshdat,
ordedat,
stradat,
ierr)
Description
The SCOTCH meshOrderCompute routine computes a block ordering of the
mesh structure pointed to by grafptr, using the mapping strategy pointed
to by stratptr, and stores its result in the ordering structure pointed to by
ordeptr.
On return, the ordering structure holds a block ordering of the given mesh
(see section 7.9.2 for a description of the ordering fields).
Return values
SCOTCH meshOrderCompute returns 0 if the ordering has been successfully
computed, and 1 else. In this latter case, the ordering arrays may however
have been partially or completely filled, but their contents are not significant.
7.10
Strategy handling routines
7.10.1
SCOTCH stratInit
Synopsis
int SCOTCH stratInit (SCOTCH Strat *
scotchfstratinit (doubleprecision (*)
integer
straptr)
stradat,
ierr)
Description
The SCOTCH stratInit function initializes a SCOTCH Strat structure so as to
make it suitable for future operations. It should be the first function to be
called upon a SCOTCH Strat structure. When the strategy data is no longer
of use, call function SCOTCH stratExit to free its internal structures.
Return values
SCOTCH stratInit returns 0 if the strategy structure has been successfully
initialized, and 1 else.
7.10.2
SCOTCH stratExit
Synopsis
void SCOTCH stratExit (SCOTCH Strat *
scotchfstratexit (doubleprecision (*)
archptr)
stradat)
Description
The SCOTCH stratExit function frees the contents of a SCOTCH Strat structure previously initialized by SCOTCH stratInit. All subsequent calls to
SCOTCH strat routines other than SCOTCH stratInit, using this structure
as parameter, may yield unpredictable results.
101
7.10.3
SCOTCH stratSave
Synopsis
int SCOTCH stratSave (const SCOTCH Strat *
FILE *
scotchfstratsave (doubleprecision (*)
integer
integer
straptr,
stream)
stradat,
fildes,
ierr)
Description
The SCOTCH stratSave routine saves the contents of the SCOTCH Strat structure pointed to by straptr to stream stream, in the form of a text string.
The methods and parameters of the strategy string depend on the type of the
strategy, that is, whether it is a bipartitioning, mapping, or ordering strategy,
and to which structure it applies, that is, graphs or meshes.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor fildes associated with the logical unit of the output file.
Return values
SCOTCH stratSave returns 0 if the strategy string has been successfully written to stream, and 1 else.
7.10.4
SCOTCH stratGraphBipart
Synopsis
int SCOTCH stratGraphBipart (SCOTCH Strat *
const char *
scotchfstratgraphbipart (doubleprecision (*)
character (*)
integer
straptr,
string)
stradat,
string,
ierr)
Description
The SCOTCH stratGraphBipart routine fills the strategy structure pointed
to by straptr with the graph bipartitioning strategy string pointed to by
string. From this point, the strategy structure can only be used as a graph
bipartitioning strategy, to be used by function SCOTCH archBuild, for instance.
When using the C interface, the array of characters pointed to by string
must be null-terminated.
Return values
SCOTCH stratGraphBipart returns 0 if the strategy string has been successfully set, and 1 else.
102
7.10.5
SCOTCH stratGraphMap
Synopsis
int SCOTCH stratGraphMap (SCOTCH Strat *
const char *
straptr,
string)
scotchfstratgraphmap (doubleprecision (*)
character (*)
integer
stradat,
string,
ierr)
Description
The SCOTCH stratGraphMap routine fills the strategy structure pointed to by
straptr with the graph mapping strategy string pointed to by string. From
this point, the strategy structure can only be used as a mapping strategy, to
be used by function SCOTCH graphMap, for instance.
When using the C interface, the array of characters pointed to by string
must be null-terminated.
Return values
SCOTCH stratGraphMap returns 0 if the strategy string has been successfully
set, and 1 else.
7.10.6
SCOTCH stratGraphOrder
Synopsis
int SCOTCH stratGraphOrder (SCOTCH Strat *
const char *
scotchfstratgraphorder (doubleprecision (*)
character (*)
integer
straptr,
string)
stradat,
string,
ierr)
Description
The SCOTCH stratGraphOrder routine fills the strategy structure pointed to
by straptr with the graph ordering strategy string pointed to by string.
From this point, the strategy structure can only be used as a graph ordering
strategy, to be used by function SCOTCH graphOrder, for instance.
When using the C interface, the array of characters pointed to by string
must be null-terminated.
Return values
SCOTCH stratGraphOrder returns 0 if the strategy string has been successfully
set, and 1 else.
103
7.10.7
SCOTCH stratMeshOrder
Synopsis
int SCOTCH stratMeshOrder (SCOTCH Strat *
const char *
straptr,
string)
scotchfstratmeshorder (doubleprecision (*)
character (*)
integer
stradat,
string,
ierr)
Description
The SCOTCH stratMeshOrder routine fills the strategy structure pointed to by
straptr with the mesh ordering strategy string pointed to by string. From
this point, strategy strat can only be used as a mesh ordering strategy, to
be used by function SCOTCH meshOrder, for instance.
When using the C interface, the array of characters pointed to by string
must be null-terminated.
Return values
SCOTCH stratMeshOrder returns 0 if the strategy string has been successfully
set, and 1 else.
7.11
Geometry handling routines
Since the Scotch project is based on algorithms that rely on topology data only,
geometry data do not play an important role in the libScotch library. They are
only relevant to programs that display graphs, such as the gout program. However,
since all routines that are used by the programs of the Scotch distributions have
an interface in the libScotch library, there exist geometry handling routines in it,
which manipulate SCOTCH Geom structures.
Apart from the routines that create, destroy or access SCOTCH Geom structures,
all of the routines in this section are input/output routines, which read or write
both SCOTCH Graph and SCOTCH Geom structures. We have chosen to define the
interface of the geometry-handling routines such that they also handle graph or
mesh topology because some external file formats mix these data, and that we
wanted our routines to be able to read their data on the fly from streams that can
only be read once, such as communication pipes. Having both aspects taken into
account in a single call makes the writing of file conversion tools, such as gcv and
mcv, very easy. When the file format from which to read or into which to write
mixes both sorts of data, the geometry file pointer can be set to NULL, as it will not
be used.
7.11.1
SCOTCH geomInit
Synopsis
int SCOTCH geomInit (SCOTCH Geom *
104
geomptr)
scotchfgeominit (doubleprecision (*)
integer
geomdat,
ierr)
Description
The SCOTCH geomInit function initializes a SCOTCH Geom structure so as to
make it suitable for future operations. It should be the first function to be
called upon a SCOTCH Geom structure. When the geometrical data is no longer
of use, call function SCOTCH geomExit to free its internal structures.
Return values
SCOTCH geomInit returns 0 if the geometrical structure has been successfully
initialized, and 1 else.
7.11.2
SCOTCH geomExit
Synopsis
void SCOTCH geomExit (SCOTCH Geom *
scotchfgeomexit (doubleprecision (*)
geomptr)
geomdat)
Description
The SCOTCH geomExit function frees the contents of a SCOTCH Geom structure
previously initialized by SCOTCH geomInit. All subsequent calls to SCOTCH
*Geom* routines other than SCOTCH geomInit, using this structure as parameter, may yield unpredictable results.
7.11.3
SCOTCH geomData
Synopsis
void SCOTCH geomData (const SCOTCH Geom *
SCOTCH Num *
double **
scotchfgeomdata (doubleprecision (*)
doubleprecision (*)
integer
integer
geomptr,
dimnptr,
geomtab)
geomdat,
indxtab,
dimnnbr,
geomidx)
Description
The SCOTCH geomData routine is a multiple accessor to the contents of
SCOTCH Geom structures.
dimnptr is the pointer to a location that will hold the number of dimensions
of the graph vertex or mesh node vertex coordinates, and will therefore be
105
equal to 1, 2 or 3. geomtab is the pointer to a location that will hold the
reference to the geometry coordinates, as defined in section 7.2.4.
Any of these pointers can be set to NULL on input if the corresponding information is not needed. Else, the reference to a dummy area can be provided,
where all unwanted data will be written.
Since there are no pointers in Fortran, a specific mechanism is used to allow
users to access the coordinate array. The scotchfgeomdata routine is passed
an integer array, the first element of which is used as a base address from
which all other array indices are computed. Therefore, instead of returning a
reference, the routine returns an integer, which represents the starting index
of the coordinate array with respect to the base input array. For instance, if
some base array myarray(1) is passed as parameter indxtab, then the first
cell of array geomtab will be accessible as myarray(geomidx). In order for
this feature to behave properly, the indxtab array must be double-precisionaligned with the geometry array. This is automatically enforced on most
systems, but some care should be taken on systems that allow one to access
data that is not double-aligned. On such systems, declaring the array after
a dummy doubleprecision array can coerce the compiler into enforcing the
proper alignment.
7.11.4
SCOTCH graphGeomLoadChac
Synopsis
int SCOTCH graphGeomLoadChac (SCOTCH Graph *
SCOTCH Geom *
FILE *
FILE *
const char *
scotchfgraphgeomloadchac (doubleprecision (*)
doubleprecision (*)
integer
integer
character (*)
grafptr,
geomptr,
grafstream,
geomstream,
string)
grafdat,
geomdat,
graffildes,
geomfildes,
string)
Description
The SCOTCH graphGeomLoadChac routine fills the SCOTCH Graph structure
pointed to by grafptr with the source graph description available from stream
grafstream in the Chaco graph format [24]. Since this graph format does
not handle geometry data, the geomptr and geomstream fields are not used,
as well as the string field.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor graffildes associated with the logical unit of the graph file.
Return values
SCOTCH graphGeomLoadChac returns 0 if the graph structure has been successfully allocated and filled with the data read, and 1 else.
106
7.11.5
SCOTCH graphGeomSaveChac
Synopsis
int SCOTCH graphGeomSaveChac (const SCOTCH Graph *
const SCOTCH Geom *
FILE *
FILE *
const char *
scotchfgraphgeomsavechac (doubleprecision (*)
doubleprecision (*)
integer
integer
character (*)
grafptr,
geomptr,
grafstream,
geomstream,
string)
grafdat,
geomdat,
graffildes,
geomfildes,
string)
Description
The SCOTCH graphGeomSaveChac routine saves the contents of the SCOTCH
Graph structure pointed to by grafptr to stream grafstream, in the Chaco
graph format [24]. Since this graph format does not handle geometry data,
the geomptr and geomstream fields are not used, as well as the string field.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor graffildes associated with the logical unit of the graph file.
Return values
SCOTCH graphGeomSaveChac returns 0 if the graph structure has been successfully written to grafstream, and 1 else.
7.11.6
SCOTCH graphGeomLoadHabo
Synopsis
int SCOTCH graphGeomLoadHabo (SCOTCH Graph *
SCOTCH Geom *
FILE *
FILE *
const char *
scotchfgraphgeomloadhabo (doubleprecision (*)
doubleprecision (*)
integer
integer
character (*)
grafptr,
geomptr,
grafstream,
geomstream,
string)
grafdat,
geomdat,
graffildes,
geomfildes,
string)
Description
The SCOTCH graphGeomLoadHabo routine fills the SCOTCH Graph structure
pointed to by grafptr with the source graph description available from stream
grafstream in the Harwell-Boeing square assembled matrix format [10]. Since
107
this graph format does not handle geometry data, the geomptr and geom
stream fields are not used. Since multiple graph structures can be encoded
sequentially within the same file, the string field contains the string representation of an integer number that codes the rank of the graph to read within
the Harwell-Boeing file. It is equal to “0” in most cases.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor graffildes associated with the logical unit of the graph file.
Return values
SCOTCH graphGeomLoadHabo returns 0 if the graph structure has been successfully allocated and filled with the data read, and 1 else.
7.11.7
SCOTCH graphGeomLoadScot
Synopsis
int SCOTCH graphGeomLoadScot (SCOTCH Graph *
SCOTCH Geom *
FILE *
FILE *
const char *
scotchfgraphgeomloadscot (doubleprecision (*)
doubleprecision (*)
integer
integer
character (*)
grafptr,
geomptr,
grafstream,
geomstream,
string)
grafdat,
geomdat,
graffildes,
geomfildes,
string)
Description
The SCOTCH graphGeomLoadScot routine fills the SCOTCH Graph and SCOTCH
Geom structures pointed to by grafptr and geomptr with the source graph
description and geometry data available from streams grafstream and geom
stream in the Scotch graph and geometry formats (see sections 5.1 and 5.3,
respectively). The string field is not used.
Fortran users must use the FNUM function to obtain the numbers of the Unix
file descriptors graffildes and geomfildes associated with the logical units
of the graph and geometry files.
Return values
SCOTCH graphGeomLoadScot returns 0 if the graph topology and geometry
have been successfully allocated and filled with the data read, and 1 else.
7.11.8
SCOTCH graphGeomSaveScot
Synopsis
108
int SCOTCH graphGeomSaveScot (const SCOTCH Graph *
const SCOTCH Geom *
FILE *
FILE *
const char *
scotchfgraphgeomsavescot (doubleprecision (*)
doubleprecision (*)
integer
integer
character (*)
grafptr,
geomptr,
grafstream,
geomstream,
string)
grafdat,
geomdat,
graffildes,
geomfildes,
string)
Description
The SCOTCH graphGeomSaveScot routine saves the contents of the SCOTCH
Graph and SCOTCH Geom structures pointed to by grafptr and geomptr to
streams grafstream and geomstream, in the Scotch graph and geometry
formats (see sections 5.1 and 5.3, respectively). The string field is not used.
Fortran users must use the FNUM function to obtain the numbers of the Unix
file descriptors graffildes and geomfildes associated with the logical units
of the graph and geometry files.
Return values
SCOTCH graphGeomSaveScot returns 0 if the graph topology and geometry
have been successfully written to grafstream and geomstream, and 1 else.
7.11.9
SCOTCH meshGeomLoadHabo
Synopsis
int SCOTCH meshGeomLoadHabo (SCOTCH Mesh *
SCOTCH Geom *
FILE *
FILE *
const char *
meshptr,
geomptr,
meshstream,
geomstream,
string)
scotchfmeshgeomloadhabo (doubleprecision (*)
doubleprecision (*)
integer
integer
character (*)
meshdat,
geomdat,
meshfildes,
geomfildes,
string)
Description
The SCOTCH meshGeomLoadHabo routine fills the SCOTCH Mesh structure
pointed to by meshptr with the source mesh description available from stream
meshstream in the Harwell-Boeing square elemental matrix format [10]. Since
this mesh format does not handle geometry data, the geomptr and geom
stream fields are not used. Since multiple mesh structures can be encoded
109
sequentially within the same file, the string field contains the string representation of an integer number that codes the rank of the mesh to read within
the Harwell-Boeing file. It is equal to “0” in most cases.
Fortran users must use the FNUM function to obtain the number of the Unix
file descriptor meshfildes associated with the logical unit of the mesh file.
Return values
SCOTCH meshGeomLoadHabo returns 0 if the mesh structure has been successfully allocated and filled with the data read, and 1 else.
7.11.10
SCOTCH meshGeomLoadScot
Synopsis
int SCOTCH meshGeomLoadScot (SCOTCH Mesh *
SCOTCH Geom *
FILE *
FILE *
const char *
meshptr,
geomptr,
meshstream,
geomstream,
string)
scotchfmeshgeomloadscot (doubleprecision (*)
doubleprecision (*)
integer
integer
character (*)
meshdat,
geomdat,
meshfildes,
geomfildes,
string)
Description
The SCOTCH meshGeomLoadScot routine fills the SCOTCH Mesh and SCOTCH
Geom structures pointed to by meshptr and geomptr with the source mesh
description and node geometry data available from streams meshstream and
geomstream in the Scotch mesh and geometry formats (see sections 5.2
and 5.3, respectively). The string field is not used.
Fortran users must use the FNUM function to obtain the numbers of the Unix
file descriptors meshfildes and geomfildes associated with the logical units
of the mesh and geometry files.
Return values
SCOTCH meshGeomLoadScot returns 0 if the mesh topology and node geometry
have been successfully allocated and filled with the data read, and 1 else.
7.11.11
SCOTCH meshGeomSaveScot
Synopsis
int SCOTCH meshGeomSaveScot (const SCOTCH Mesh *
const SCOTCH Geom *
FILE *
FILE *
const char *
110
meshptr,
geomptr,
meshstream,
geomstream,
string)
scotchfmeshgeomsavescot (doubleprecision (*)
doubleprecision (*)
integer
integer
character (*)
meshdat,
geomdat,
meshfildes,
geomfildes,
string)
Description
The SCOTCH meshGeomSaveScot routine saves the contents of the SCOTCH
Mesh and SCOTCH Geom structures pointed to by meshptr and geomptr to
streams meshstream and geomstream, in the Scotch mesh and geometry
formats (see sections 5.2 and 5.3, respectively). The string field is not used.
Fortran users must use the FNUM function to obtain the numbers of the Unix
file descriptors meshfildes and geomfildes associated with the logical units
of the mesh and geometry files.
Return values
SCOTCH meshGeomSaveScot returns 0 if the mesh topology and node geometry
have been successfully written to meshstream and geomstream, and 1 else.
7.12
Error handling routines
The handling of errors that occur within library routines is often difficult, because
library routines should be able to issue error messages that help the application
programmer to find the error, while being compatible with the way the application
handles its own errors.
To match these two requirements, all the error and warning messages produced by the routines of the libScotch library are issued using the user-definable
variable-length argument routines SCOTCH errorPrint and SCOTCH errorPrintW.
Thus, one can redirect these error messages to his own error handling routines, and
can choose if he wants his program to terminate on error or to resume execution
after the erroneous function has returned.
In order to free the user from the burden of writing a basic error handler
from scratch, the libscotcherr.a library provides error routines that print error
messages on the standard error stream stderr and return control to the application. Application programmers who want to take advantage of them have to add
-lscotcherr to the list of arguments of the linker, after the -lscotch argument.
7.12.1
SCOTCH errorPrint
Synopsis
void SCOTCH errorPrint (const char * const
errstr, ...)
Description
The SCOTCH errorPrint function is designed to output a variable-length argument error string to some stream.
111
7.12.2
SCOTCH errorPrintW
Synopsis
void SCOTCH errorPrintW (const char * const
errstr, ...)
Description
The SCOTCH errorPrintW function is designed to output a variable-length
argument warning string to some stream.
7.12.3
SCOTCH errorProg
Synopsis
void SCOTCH errorProg (const char *
progstr)
Description
The SCOTCH errorProg function is designed to be called at the beginning of a
program or of a portion of code to identify the place where subsequent errors
take place. This routine is not reentrant, as it is only a minor help function.
It is defined in libscotcherr.a and is used by the standalone programs of
the Scotch distribution.
7.13
Miscellaneous routines
7.13.1
SCOTCH randomReset
Synopsis
void SCOTCH randomReset (void)
scotchfrandomreset ()
Description
The SCOTCH randomReset routine resets the seed of the pseudo-random generator used by the graph partitioning routines of the libScotch library. Two
consecutive calls to the same libScotch partitioning routines, and separated
by a call to SCOTCH randomReset, will always yield the same results, as if the
equivalent standalone Scotch programs were used twice, independently, to
compute the results.
112
MeTiS compatibility library
7.14
The MeTiS compatibility library provides stubs which redirect some calls to MeTiS
routines to the corresponding Scotch counterparts. In order to use this feature,
the only thing to do is to re-link the existing software with the libscotchmetis
library, and eventually with the original MeTiS library if the software uses MeTiS
routines which do not need to have Scotch equivalents, such as graph transformation routines. In that latter case, the “-lscotchmetis” argument must be placed
before the “-lmetis” one (and of course before the “-lscotch” one too), so that
routines that are redefined by Scotch are chosen instead of their MeTiS counterpart. When no other MeTiS routines than the ones redefined by Scotch are used,
the “-lmetis” argument can be omitted. See Section 9 for an example.
7.14.1
METIS EdgeND
Synopsis
void METIS EdgeND (const
const
const
const
const
int *
int *
metis edgend (integer
integer
integer
integer
integer
integer
integer
int *
int *
int *
int *
int *
const
const
(*)
(*)
(*)
(*)
(*)
const
const
const
const
const
n,
xadj,
adjncy,
numflag,
options,
perm,
iperm)
n,
xadj,
adjncy,
numflag,
options,
perm,
iperm)
Description
The METIS EdgeND function performs a nested dissection ordering of the graph
passed as arrays xadj and adjncy, using the default Scotch ordering strategy. The options array is not used. The perm and iperm arrays have the
opposite meaning as in Scotch: the MeTiS perm array holds what is called
“inverse permutation” in Scotch, while iperm holds what is called “direct
permutation” in Scotch.
While Scotch has also both node and edge separation capabilities, all of
the three MeTiS stubs METIS EdgeND, METIS NodeND and METIS NodeWND call
the same Scotch routine, which uses the Scotch default ordering strategy
proved to be efficient in most cases.
7.14.2
METIS NodeND
Synopsis
113
void METIS NodeND (const
const
const
const
const
int *
int *
metis nodend (integer
integer
integer
integer
integer
integer
integer
int *
int *
int *
int *
int *
const
const
const
const
const
const
const
n,
xadj,
adjncy,
numflag,
options,
perm,
iperm)
n,
xadj,
adjncy,
numflag,
options,
perm,
iperm)
(*)
(*)
(*)
(*)
(*)
Description
The METIS NodeND function performs a nested dissection ordering of the graph
passed as arrays xadj and adjncy, using the default Scotch ordering strategy. The options array is not used. The perm and iperm arrays have the
opposite meaning as in Scotch: the MeTiS perm array holds what is called
“inverse permutation” in Scotch, while iperm holds what is called “direct
permutation” in Scotch.
While Scotch has also both node and edge separation capabilities, all of
the three MeTiS stubs METIS EdgeND, METIS NodeND and METIS NodeWND call
the same Scotch routine, which uses the Scotch default ordering strategy
proved to be efficient in most cases.
7.14.3
METIS NodeWND
Synopsis
void METIS NodeWND (const
const
const
const
const
const
int *
int *
metis nodwend (integer
integer
integer
integer
integer
integer
integer
integer
int *
int *
int *
int *
int *
int *
const
const
(*)
(*)
(*)
(*)
(*)
(*)
const
const
const
const
const
const
n,
xadj,
adjncy,
vwgt,
numflag,
options,
perm,
iperm)
114
n,
xadj,
adjncy,
vwgt,
numflag,
options,
perm,
iperm)
Description
The METIS NodeWND function performs a nested dissection ordering of the
graph passed as arrays xadj, adjncy and vwgt, using the default Scotch
ordering strategy. The options array is not used. The perm and iperm
arrays have the opposite meaning as in Scotch: the MeTiS perm array holds
what is called “inverse permutation” in Scotch, while iperm holds what is
called “direct permutation” in Scotch.
While Scotch has also both node and edge separation capabilities, all of
the three MeTiS stubs METIS EdgeND, METIS NodeND and METIS NodeWND call
the same Scotch routine, which uses the Scotch default ordering strategy
proved to be efficient in most cases.
7.14.4
METIS PartGraphKway
Synopsis
void METIS PartGraphKway (const
const
const
const
const
const
const
const
const
int *
int *
metis partgraphkway (integer
integer
integer
integer
integer
integer
integer
integer
integer
integer
integer
int *
int *
int *
int *
int *
int *
int *
int *
int *
const
const
(*)
(*)
(*)
(*)
(*)
(*)
const
const
const
const
const
const
const
const
const
n,
xadj,
adjncy,
vwgt,
adjwgt,
wgtflag,
numflag,
nparts,
options,
edgecut,
part)
n,
xadj,
adjncy,
vwgt,
adjwgt,
wgtflag,
numflag,
nparts,
options,
edgecut,
part)
Description
The METIS PartGraphKway function performs a mapping onto the complete
graph of the graph represented by arrays xadj, adjncy, vwgt and adjwgt,
using the default Scotch mapping strategy. The options array is not used.
The part array has the same meaning as the parttab array of Scotch.
All of the three MeTiS stubs METIS PartGraphKway, METIS PartGraph
Recursive and METIS PartGraphVKway call the same Scotch routine, which
115
uses the Scotch default mapping strategy proved to be efficient in most cases.
7.14.5
METIS PartGraphRecursive
Synopsis
void METIS PartGraphRecursive (const
const
const
const
const
const
const
const
const
int *
int *
metis partgraphrecursive (integer
integer
integer
integer
integer
integer
integer
integer
integer
integer
integer
int *
int *
int *
int *
int *
int *
int *
int *
int *
const
const
(*)
(*)
(*)
(*)
(*)
(*)
const
const
const
const
const
const
const
const
const
n,
xadj,
adjncy,
vwgt,
adjwgt,
wgtflag,
numflag,
nparts,
options,
edgecut,
part)
n,
xadj,
adjncy,
vwgt,
adjwgt,
wgtflag,
numflag,
nparts,
options,
edgecut,
part)
Description
The METIS PartGraphRecursive function performs a mapping onto the complete graph of the graph represented by arrays xadj, adjncy, vwgt and
adjwgt, using the default Scotch mapping strategy. The options array
is not used. The part array has the same meaning as the parttab array
of Scotch. To date, the computation of the edgecut field requires extra
processing, which increases running time to a small extent.
All of the three MeTiS stubs METIS PartGraphKway, METIS PartGraph
Recursive and METIS PartGraphVKway call the same Scotch routine, which
uses the Scotch default mapping strategy proved to be efficient in most cases.
7.14.6
METIS PartGraphVKway
Synopsis
116
void METIS PartGraphVKway (const
const
const
const
const
const
const
const
const
int *
int *
metis partgraphvkway (integer
integer
integer
integer
integer
integer
integer
integer
integer
integer
integer
int *
int *
int *
int *
int *
int *
int *
int *
int *
const
const
(*)
(*)
(*)
(*)
(*)
(*)
const
const
const
const
const
const
const
const
const
n,
xadj,
adjncy,
vwgt,
vsize,
wgtflag,
numflag,
nparts,
options,
volume,
part)
n,
xadj,
adjncy,
vwgt,
vsize,
wgtflag,
numflag,
nparts,
options,
volume,
part)
Description
The METIS PartGraphVKway function performs a mapping onto the complete
graph of the graph represented by arrays xadj, adjncy, vwgt and vsize, using
the default Scotch mapping strategy. The options array is not used. The
part array has the same meaning as the parttab array of Scotch.
Since Scotch does not have methods for explicitely reducing the communication volume according to the metric of METIS PartGraphVKway, this routine
creates a temporary edge weight array such that each edge (u, v) receives a
weight equal to mboxvsize(u) + mboxvsize(v). Consequently, edges which
are incident to highly communicating vertices will be less likely to be cut.
However, the communication volume value returned by this routine is exactly the one which would be returned by MeTiS with respect to the output
partition. Users interested in minimizing the exact communication volume
should consider using hypergraphs, implemented in Scotch as meshes (see
Section 7.2.3).
All of the three MeTiS stubs METIS PartGraphKway, METIS PartGraph
Recursive and METIS PartGraphVKway call the same Scotch routine, which
uses the Scotch default mapping strategy proved to be efficient in most cases.
8
Installation
Version 5.1 of the Scotch software package is distributed as free/libre software
under the CeCILL-C free/libre software license [6], which is very similar to the
GNU LGPL license. Therefore, it is no longer distributed as a set of binaries, but
instead in the form of a source distribution, which can be downloaded from the
117
Scotch web page at http://www.labri.fr/~pelegrin/scotch/ .
The extraction process will create a scotch 5.1 directory, containing several
subdirectories and files. Please refer to the files called LICENSE EN.txt or LICENCE
FR.txt, as well as file INSTALL EN.txt, to see under which conditions your
distribution of Scotch is licensed and how to install it.
To enable the use of POSIX threads in some routines, the SCOTCH PTHREAD flag
must be set. If your MPI implementation is not thread-safe, make sure this flag is
not defined at compile time.
To enable on-the-fly compression and decompression of various formats, the
relevant flags must be defined. These flags are COMMON FILE COMPRESS BZ2 for
bzip2 (de)compression, COMMON FILE COMPRESS GZ for gzip (de)compression, and
COMMON FILE COMPRESS LZMA for lzma decompression. Note that the corresponding development libraries must be installed on your system before compile time,
and that compressed file handling can take place only on systems which support
multi-threading or multi-processing. In the first case, you must set the SCOTCH
PTHREAD flag in order to take advantage of these features.
On Linux systems, the development libraries to install are libbzip2 1devel for the bzip2 format, zlib1-devel for the gzip format, and liblzma0devel for the lzma format. The names of the libraries may vary according to
operating systems and library versions. Ask your system engineer in case of trouble.
The integer values handled by Scotch are based by default on the int C type,
corresponding to the INTEGER Fortran type, both of which being of the size of a
machine word. To coerce the length of the Scotch integer type to 32 or 64 bits,
one can use the INTSIZE32 or INTSIZE64 flags, respectively, or else the “-DINT=”
definition, at compile time. For instance, adding “-DINT=long” to the CFLAGS
variable in the Makefile.inc file to be placed at the root of the source tree will
make all SCOTCH Num integers become long C integers.
Whenever doing so, make sure to use integer types of equivalent length to
declare variables passed to Scotch routines from caller C and Fortran procedures.
Also, because of API conflicts, the MeTiS compatibility library will not be usable.
It is usually safer and cleaner to tune your C and Fortran compilers to make
them interpret int and INTEGER types as 32 or 64 bit values, than to use the
aforementioned flags and coerce type lengths in your own code.
All Scotch users are welcome to send a mail to the author so that they can be
added to the Scotch mailing list, and be automatically informed of new releases
and publications.
9
Examples
This section contains chosen examples destined to show how the programs of the
Scotch project interoperate and can be combined. It is supposed that the current
directory is directory “scotch 5.1” of the Scotch distribution. Character “%”
represents the shell prompt.
• Partition source graph brol.grf into 7 parts, and save the result to file
/tmp/brol.map.
118
% echo cmplt 7 > /tmp/k7.tgt
% gmap brol.grf /tmp/k7.tgt /tmp/brol.map
This can also be done in a single piped command:
% echo cmplt 7 | gmap brol.grf - /tmp/brol.map
If compressed data handling is enabled, read the graph as a gzip compressed
file, and output the mapping as a bzip2 file, on the fly:
% echo cmplt 7 | gmap brol.grf.gz - /tmp/brol.map.bz2
• Partition source graph brol.grf into two uneven parts of respective weights
4
7
11 and 11 , and save the result to file /tmp/brol.map.
% echo cmpltw 2 4 7 > /tmp/k2w.tgt
% gmap brol.grf /tmp/k2w.tgt /tmp/brol.map
This can also be done in a single piped command:
% echo cmpltw 2 4 7 | gmap brol.grf - /tmp/brol.map
If compressed data handling is enabled, use gzip compressed streams on the
fly:
% echo cmpltw 2 4 7 | gmap brol.grf.gz - /tmp/brol.map.gz
• Map a 32 by 32 bidimensional grid source graph onto a 256-node hypercube,
and save the result to file /tmp/brol.map.
% gmk m2 32 32 | gmap - tgt/h8.tgt /tmp/brol.map
• Build the Open Inventor file graph.iv that contains the display of a
source graph the source and geometry files of which are named graph.grf
and graph.xyz.
% gout -Mn -Oi graph.grf graph.xyz - graph.iv
Although no mapping data is required because of the “-Mn” option, note the
presence of the dummy input mapping file name “-”, which is needed to
specify the output visualization file name.
• Given the source and geometry files graph.grf and graph.xyz of a source
graph, map the graph on a 8 by 8 bidimensional mesh and display the
mapping result on a color screen by means of the public-domain ghostview
PostScript previewer.
% gmap graph.grf tgt/m8x8.tgt | gout graph.grf graph.xyz
’-Op{c,f,l}’ | ghostview -
119
• Build a 24-node Cube-Connected-Cycles graph target architecture which will
be frequently used. Then, map compressed source file graph.grf.gz onto it,
and save the result to file /tmp/brol.map.
% amk ccc 3 | acpl - /tmp/ccc3.tgt
% gunzip -c graph.grf.gz | gmap - /tmp/ccc3.tgt /tmp/brol.map
To speed up target architecture loading in the future, the decompositiondefined target architecture is compiled by means of acpl.
• Build an architecture graph which is the subgraph of the 8-node de Bruijn
graph restricted to vertices labeled 1, 2, 4, 5, 6, map graph graph.grf onto
it, and save the result to file /tmp/brol.map.
% (gmk ub2 3; echo 5 1 2 4 5 6) | amk grf -L | gmap graph.grf /tmp/brol.map
Note how the two input streams of program amk grf (that is, the de Bruijn
source graph and the five-elements vertex label list) are concatenated into a
single stream to be read from the standard input.
• Compile and link the user application brol.c with the libScotch library,
using the default error handler.
% cc brol.c -o brol -lscotch -lscotcherr -lm
Note that the mathematical library should also be included, after all of the
Scotch libraries.
• Recompile a program that used MeTiS so that it uses Scotch instead.
% cc brol.c -o brol -I${metisdir} -lscotchmetis -lscotch
-lscotcherr -lmetis -lm
Note that the “-lscotchmetis” option must be placed before the “-lmetis”
one, so that routines that are redefined by Scotch are selected instead of
their MeTiS counterpart. When no other MeTiS routines than the ones redefined by Scotch are used, the “-lmetis” option can be omitted. The
“-I${metisdir}” option may be necessary to provide the path to the original metis.h include file, which contains the prototypes of all of the MeTiS
routines.
10
Adding new features to Scotch
Since Scotch is free/libre software, users have the ability to add new features to it.
Moreover, as Scotch is intended to be a testbed for new partitioning and ordering
algorithms, it has been developed in a very modular way, to ease the development
and inclusion of new partitioning and ordering methods to be called within Scotch
strategies.
All of the source code for partitioning and ordering methods for graphs and
meshes is located in the src/libscotch/ source subdirectory. Source file names
have a very regular pattern, based on the internal data structures they handle.
120
10.1
Graphs and meshes
The basic structures in Scotch are the Graph and Mesh structures, which model
a simple symmetric graph the definition of which is given in file graph.h, and a
simple mesh, in the form of a bipartite graph, the definition of which is given in
file mesh.h, respectively. From this structure are derived enriched graph and mesh
structures:
• Bgraph, in file bgraph.h: graph with bipartition, that is, edge separation,
information attached to it;
• Kgraph, in file kgraph.h: graph with mapping information attached to it;
• Hgraph, in file hgraph.h: graph with halo information attached to it, for
computing graph orderings;
• Vgraph, in file vgraph.h: graph with vertex bipartition information attached
to it;
• Hmesh, in file hmesh.h: mesh with halo information attached to it, for computing mesh orderings;
• Vmesh, in file vmesh.h: graph with vertex bipartition information attached to
it.
As version 5.1 of the libScotch does not provide mesh mapping capabilities, neither Bmesh nor Kmesh structures have been defined to date, but this work is in
progress, and these features should be available in the upcoming releases.
All of the structures are in fact defined as typedefed types.
10.2
Methods and partition data
Methods are routines which take one of the above structures as input, and update
the fields of the given structure according to the implemented algorithm. Initial
methods will behave irrespective of the former values of the structure (like graph
growing methods, which compute partitions from scratch), while refinement methods must be provided an existing partition to improve.
In addition to the topological description of the underlying graph, the working
graph and mesh structures comprise variables describing the current state of the
vertex or edge partition. In all cases is provided a partition array called parttax,
of size equal to the number of graph vertices, which tells which part every vertex
is assigned to. Other variables comprise the communication load and the load
imbalance of the current cut, that is, all of the data necessary to measure the
quality of a partition. Some other data are also often provided, such as the number
of vertices in each part and the list of frontier vertices. They are not relevant to
measure the quality of the partition, but to improve the speed of computations.
They are used for instance in the multi-level algorithms to compute incremental
updates of the current partition state, without having to recompute these values
from scratch by considering all of the graph vertices. Implementers of new methods
are highly encouraged to use these variables to speed-up their computations, taking
examples on typical algorithms such as the multi-level or Fiduccia-Mattheyses ones.
121
10.3
Adding a new method to Scotch
We will assume in this section that the new method to add is a graph separation
method. The procedure explained below is exactly the same for graph bipartitioning, graph mapping, graph ordering, mesh separation, or mesh ordering methods.
Please proceed as explained below.
1. Write the code of the method itself. First, choose a free two-letter code to
describe your method, say “xy”. In the libscotch source directory, create
files vgraph separate xy.c and vgraph separate xy.h, basing on existing
files such as vgraph separate gg.c and vgraph separate gg.h, for instance.
If the method is complex, it can be split across several other files, which will
be named vgraph separate xy firstmodulename.c, vgraph separate xy
secondmodulename.c, eventually with matching header files.
If the method has parameters, create a structure called VgraphSeparateXy
Param, which contains fields of types that can be handled by the strategy
parser, such as the INT generic integer type (see below), or double, for instance.
The execution of your method should result in the setting or in the updating
of the Vgraph structure that is passed to it. See its definition in vgraph.h
and read several simple graph separation methods, such as vgraph separate
zr.c, to figure out what all of its parameters mean.
At the end of your method, always call, when the SCOTCH DEBUG VGRAPH2
debug flag is set, the vgraphCheck routine, to avoid the spreading of eventual
bugs to other parts of the libScotch library.
2. Add the method to the parser tables. The files to update are vgraph
separate st.c and vgraph separate st.h, where “st” stands for “strategy”.
First, edit vgraph separate st.h. In the VgraphSeparateStMethodType
enumeration, add a line for your new method VGRAPHSEPASTMETHXY. Then,
edit vgraph separate st.c, where all of the remaining actions take place.
In the top of the file, add a #include directive to include vgraph separate
xy.h.
If the method has parameters, create a vgraphseparatedefaultxy C union,
basing on an existing one, and fill it with the default values of your method
parameters.
In the vgraphseparatestmethtab method array, add a line for the new
method. To do so, choose a free single-letter code that will be used to designate the new method in strategy strings. If the method has parameters, the
last field should be a pointer to the default structure, else it should be set to
NULL.
If the method has parameters, update the vgraphseparatestparatab parameter array. Add one data block per parameter. The first field is the name
of the method to which the parameter applies, that is, VGRAPHSEPASTMETH
XY. The second field is the type of the parameter, which can be:
• STRATPARAMCASE: the support type is an int. It receives the index in the
case string, which is provided as the last field of the parameter line, of
the given case character;
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• STRATPARAMDOUBLE: the support type is a double;
• STRATPARAMINT: the support type is an INT, which is the generic integer type handled internally by Scotch. This type has variable extent,
depending on compilation flags, as described in Section 7.1.4;
• STRATPARAMSTRING: a (small) character string;
• STRATPARAMSTRAT: strategy. For instance, the graph ordering method
by nested dissection takes a vertex partitioning strategy as one of its
parameters, to compute the vertex separators.
The fourth and fifth fields are the address of the location of the default structure and the address of the parameter within this default structure, respectively. From these two values can be computed at run time the offset of the
parameter within any instance of the parameter structure, which is used to
fill the actual structures in the parsed strategy evaluation tree. The value of
the sixth parameter depends on the type of the parameter. It should be NULL
for STRATPARAMDOUBLE and STRATPARAMINT parameters, points to the string
of available case letters for STRATPARAMCASE parameters, points to the target
string buffer for STRATPARAMSTRING parameters, and points to the relevant
method parsing table for STRATPARAMSTRAT parameters.
3. Edit the makefile of the libScotch source directory to enable the compilation
and linking of the method. Depending on libScotch versions, this makefile
is either called Makefile or make gen.
4. Compile in debug mode and experiment with your routine, by creating strategies that contain its single-letter code.
5. To change the default strategy string used by the libScotch library, update file library graph order.c, since it is the graph ordering routine which
makes use of graph vertex separation methods to compute separators for the
nested dissection ordering method.
10.4
Licensing of new methods and of derived works
According to the terms of the CeCILL-C license [6] under which the Scotch
software package is distributed, the works that are carried out to improve and
extend the libScotch library must be licensed under the same terms. Basically, it
means that you will have to distribute the sources of your new methods, along with
the sources of Scotch, to any recipient of your modified version of the libScotch,
and that you grant these recipients the same rights of update and redistribution
as the ones that are given to you under the terms of CeCILL-C. Please read it
carefully to know what you can do and cannot do with the Scotch distribution.
You should have received a copy of the CeCILL-C license along with the Scotch
distribution; if not, please browse the CeCILL website at http://www.cecill.
info/licenses.en.html.
Credits
I wish to thank all of the following people:
123
• Patrick Amestoy collaborated to the design of the Halo Approximate Minimum Degree algorithm [49] that had been embedded into Scotch 3.3, and
gave me versions of his Approximate Minimum Degree algorithm, available
since version 3.2, and of his Halo Approximate Minimum Fill algorithm, available since version 3.4. He designed the mesh versions of the approximate minimum degree and approximate minimum fill algorithms, which are available
since version 4.0;
• Alex Pothen kindly gave me a version of his Multiple Minimum Degree algorithm, which was embedded into Scotch from version 3.2 to version 3.4;
• Luca Scarano, visiting Erasmus student from the Universitá degli Studi di
Bologna, coded the multi-level graph algorithm in Scotch 3.1;
• Yves Secretan contributed to the MinGW32 port;
• David Sherman proofread version 3.2 of this manual.
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