Terminology
Availability
The PGI 10.0 Fortran & C Accelerator compilers are available only on x86 processor-based workstations and servers with an attached NVIDIA CUDA-enabled GPU or Tesla card. These compilers target all platforms that
PGI supports except 64-bit Mac OS X. All examples included in this chapter are developed and presented on such a platform. For a list of supported GPUs, refer to the Accelerator Installation and Supported Platforms list in the latest PGI Release Notes.
User-directed Accelerator Programming
In user-directed accelerator programming the user specifies the regions of a host program to be targeted for offloading to an accelerator device. The bulk of a user’s program, as well as regions containing constructs that are not supported on the targeted accelerator, are executed on the host. This chapter concentrates on specification of loops and regions of code to be offloaded to an accelerator.
Features Not Covered or Implemented
This chapter does not describe features or limitations of the host programming environment as a whole.
Further, it does not cover automatic detection and offloading of regions of code to an accelerator by a compiler or other tool. While future versions of the PGI compilers may allow for automatic offloading or multiple accelerators of different types, these features are not currently supported.
Terminology
Clear and consistent terminology is important in describing any programming model. This section provides definitions of the terms required for you to effectively use this chapter and the associated programming model.
Accelerator a special-purpose co-processor attached to a CPU and to which the CPU can offload data and executable kernels to perform compute-intensive calculations.
Compute intensity for a given loop, region, or program unit, the ratio of the number of arithmetic operations performed on computed data divided by the number of memory transfers required to move that data between two levels of a memory hierarchy.
Compute region a region defined by an Accelerator compute region directive. A compute region is a structured block containing loops which are compiled for the accelerator. A compute region may require device memory to be allocated and data to be copied from host to device upon region entry, and data to be copied from device to host memory and device memory deallocated upon exit. Compute regions may not contain other compute regions or data regions.
CUDA stands for Compute Unified Device Architecture; the CUDA environment from NVIDIA is a C-like programming environment used to explicitly control and program an NVIDIA GPU.
Data region a region defined by an Accelerator data region directive, or an implicit data region for a function or subroutine containing Accelerator directives. Data regions typically require device memory to be allocated
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Chapter 7. Using an Accelerator and data to be copied from host to device memory upon entry, and data to be copied from device to host memory and device memory deallocated upon exit. Data regions may contain other data regions and compute regions.
Device a general reference to any type of accelerator.
Device memory memory attached to an accelerator which is physically separate from the host memory.
Directive in C, a #pragma, or in Fortran, a specially formatted comment statement that is interpreted by a compiler to augment information about or specify the behavior of the program.
DMA
Direct Memory Access, a method to move data between physically separate memories; this is typically performed by a DMA engine, separate from the host CPU, that can access the host physical memory as well as an IO device or GPU physical memory.
GPU a Graphics Processing Unit; one type of accelerator device.
GPGPU
General Purpose computation on Graphics Processing Units.
Host the main CPU that in this context has an attached accelerator device. The host CPU controls the program regions and data loaded into and executed on the device.
Loop trip count the number of times a particular loop executes.
OpenCL - Open Compute Language a proposed standard C-like programming environment similar to CUDA that enables portable low-level general-purpose programming on GPUs and other accelerators.
Private data with respect to an iterative loop, data which is used only during a particular loop iteration. With respect to a more general region of code, data which is used within the region but is not initialized prior to the region and is re-initialized prior to any use after the region.
Region a structured block identified by the programmer or implicitly defined by the language. Certain actions may occur when program execution reaches the start and end of a region, such as device memory allocation or data movement between the host and device memory. Loops in a compute region are targeted for execution on the accelerator.
Structured block in C, an executable statement, possibly compound, with a single entry at the top and a single exit at the bottom. In Fortran, a block of executable statements with a single entry at the top and a single exit at the bottom.
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