PGPROF pgcollect. STMicroelectronics PGI

Below you will find brief information for PGI. Parallel Fortran, C and C++ compilers are designed for scientists and engineers. The guide provides details on optimizing and parallelizing code, using directives and pragmas, and more.

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Profiling Accelerator Kernels

With 'N'

–tp

values and two

–ta

values, the compiler generates up to N+1 versions of the subprogram. It first generates up to N versions, for each

–tp

value, ignoring the accelerator regions, which is equivalent to using

–ta=host

. It then generates one additional version with the accelerator target.

Profiling Accelerator Kernels

This release supports the command line option:

-ta=nvidia,time

The time

suboption links in a timer library, which collects and prints out simple timing information about the accelerator regions and generated kernels.

Example 7.1. Accelerator Kernel Timing Data bb04.f90

15: region entered 1 times

time(us): total=1490738

init=1489138 region=1600

kernels=155 data=1445

w/o init: total=1600 max=1600

min=1600 avg=1600

18: kernel launched 1 times

time(us): total=155 max=155 min=155 avg=155

In this example, a number of things are occurring:

• For each accelerator region, the file name

/proj/qa/tests/accel/bb04.f90

and subroutine or function name s1

is printed, with the line number of the accelerator region, which in the example is

• The library counts how many times the region is entered (

in the example) and the microseconds spent in the region (in this example

1490738

), which is split into initialization time (in this example

1489138

) and execution time (in this example

1600

• The execution time is then divided into kernel execution time and data transfer time between the host and

GPU.

• For each kernel, the line number is given, (

in the example), along with a count of kernel launches, and the total, maximum, minimum, and average time spent in the kernel, all of which are 155 in this example.