PGI announced a new release of their compiler suite. The big news around version 10.4 is their support for the new NVIDIA Fermi GPU architecture. They provide full support for CUDA Fortran and add support for allocatable device arrays within Fortran modules along with several API enhancements.
With PGI 10.4, HPC users can create highly optimized heterogeneous multi-core applications for the latest CPUs from Intel and AMD in combination with the latest generation of GPUs from NVIDIA,” said Douglas Miles, director The Portland Group. “Efficiently using all available host cores for certain parts of an application while accelerating other portions on GPUs is the key to squeezing maximum performance out of today’s GPU-enabled workstations and cluster nodes. With Fermi’s improvement in double-precision performance, we expect a big increase in the number and type of applications that benefit from GPU acceleration.”
The PGI 10.4 release adds several ease-of-use features, including the use of PGI Unified Binary technology to build one version of an application that will run on any CUDA-enabled GPU. With PGI 10.4 compilers, programmers can automatically generate code that works and is optimized for both a Tesla C1060 GPU or the new Tesla C2050 GPU.
A large part of the success of Tesla GPUs in the HPC space can be attributed to the quality of the development tools from NVIDIA and its partners,” said Sanford Russell, general manager, GPU Computing at NVIDIA. “This announcement from PGI, building on the tools already in the market, is more evidence of the increasing momentum behind GPU computing in general and our CUDA architecture in particular.”
For more info on the new compiler release, check out their full release here.