An increasing portion of the top supercomputers in the world, including Blue Waters, have heterogeneous CPU-GPU computational units. While a handful of the science teams can already use GPUs in their production applications, there is still significant room for growing use. This program for enabling the science teams to make effective use of GPUs consists of two major components. The first is to make full use of vendor and community compiler technology, now defined by the OpenACC, OpenCL and C++AMP standards, introduce accelerator-based library capabilities for the science teams' applications, and provide support and enhancement for GPU-enabled performance and analysis tools. This will significantly reduce the programming effort and enhance code maintainability associated with the use of GPUs.

 

The second aspect is to provide expert support to the science teams through hands-on workshops and individualized collaboration programs. The goal of these efforts is not to develop new compiler technology but rather to help science teams take advantage of the most promising, mature, or experimental compiler-associated capabilities from Cray, NVIDIA, MultcoreWare, the University of Illinois, and other institutions, such as the Barcelona Supercomputing Center.

 

Furthermore, the activity will provide detailed feedback to OpenACC compiler providers in order to allow them to enable the compilers to produce more efficient code. In addition to the OpenACC-compliant, OpenMP-like compiler from Cray, the PGI FORTRAN compiler, and the Thrust C++ template library from NVIDIA, this project will provide and improve the C++AMP Compiler and the MxPA OpenCL Compiler to reduce the barrier to using the GPUs in the Cray system.