NVIDIA and PGI are offering “PGI Accelerator with OpenACC” free to academia (or 90 day trial for commercial users) under the banner “NVIDIA OpenACC Toolkit”. It’s about time!
Modern computing hardware is all about parallelism. This is because we essentially hit the wall several years ago on increasing core clock frequency to speedup serial code execution. The transistor count has continued to follow Moore’s Law (doubling every 1.5-2 years) but these transistors have mostly gone into multiple cores, vector units, memory controllers, etc. on a single die. To utilize this hardware, software needs to be written to take advantage of it, i.e. you have to go parallel.
I’m going to walk you through a basic install and configuration for a development system to do CUDA and OpenACC GPU programming. This is not a detailed howto but if you have some linux admin skills it will be a reasonable guide to get you started. We’ll do a basic NVIDIA GPU programming setup including CentOS 6.5, CUDA development environment and a PGI compiler setup with OpenACC. The most interesting part may be the OpenACC setup. OpenACC is a relatively new option for GPU programming and allows for a directive (pragma) based coding model.