The ShARC HPC cluster was decommissioned on the 30th of November 2023 at 17:00. It is no longer possible for users to access that cluster.
The PGI Compiler suite offers C, C++ and Fortran Compilers. For full details of the features of this compiler suite see PGI’s website.
Making the PGI Compilers available
After connecting to Bessemer (see Establishing a SSH connection), start an interactive session with the
srun --pty bash -i command.
You can then activate a specific version of the compiler suite using one of:
module load PGI/19.1-GCC-8.2.0-2.31.1 module load PGI/18.10-GCC-6.4.0-2.28
Once you’ve loaded the module, you can check the version with:
To compile a C hello world example into an executable called
hello using the PGI C compiler
pgcc hello.c -o hello
To compile a C++ hello world example into an executable called
hello using the PGI C++ compiler
pgc++ hello.cpp -o hello
To compile a Fortran hello world example into an executable called
hello using the PGI Fortran compiler
pgf90 hello.f90 -o hello
Compiling on the GPU using the PGI Compiler
Start an interactive GPU session (Interactive use of the GPUs) and the following module command
module load PGI/19.1-GCC-8.2.0-2.31.1
The PGI compilers have several features that make them interesting to users of GPU hardware:-
OpenACC is a relatively new way of programming GPUs that can be significantly simpler to use than low-level language extensions such as CUDA or OpenCL. From the OpenACC website :
The OpenACC Application Program Interface describes a collection of compiler directives to specify loops and regions of code in standard C, C++ and Fortran to be offloaded from a host CPU to an attached accelerator. OpenACC is designed for portability across operating systems, host CPUs, and a wide range of accelerators, including APUs, GPUs, and many-core coprocessors.
The directives and programming model defined in the OpenACC API document allow programmers to create high-level host+accelerator programs without the need to explicitly initialize the accelerator, manage data or program transfers between the host and accelerator, or initiate accelerator startup and shutdown.
For more details concerning OpenACC using the PGI compilers, see The PGI OpenACC website.
In mid 2009, PGI and NVIDIA cooperated to develop CUDA Fortran. CUDA Fortran includes a Fortran 2003 compiler and tool chain for programming NVIDIA GPUs using Fortran.
NVIDIA CUDA was developed to enable offloading computationally intensive kernels to massively parallel GPUs. Through API function calls and language extensions, CUDA gives developers explicit control over the mapping of general-purpose computational kernels to GPUs, as well as the placement and movement of data between an x86 processor and the GPU.
The PGI CUDA C/C++ compiler for x86 platforms allows developers using CUDA to compile and optimize their CUDA applications to run on x86-based workstations, servers and clusters with or without an NVIDIA GPU accelerator. When run on x86-based systems without a GPU, PGI CUDA C applications use multiple cores and the streaming SIMD (Single Instruction Multiple Data) capabilities of Intel and AMD CPUs for parallel execution.
Source archives for PGI compilers can be found and downloaded for those registered at: https://www.pgroup.com/support/release_archive.php
These archives are then added in the Easybuild media directory:
Version 19.1 was installed using the
PGI-19.1-GCC-8.2.0-2.31.1.eb easyconfig. Post installation the module file was amended with an additional line to provide the licence server address as follows:
prepend-path PGROUPD_LICENSE_FILE /usr/local/packages/common/licenses/pgi.lic
Version 18.10 was installed using the
PGI-18.10-GCC-6.4.0-2.28.eb easyconfig. Post installation the module file was amended with an additional line to provide the licence server address as with Version 19.1 .