Supercomputers have long been an indispensable, albeit expensive, tool for researchers who need to make sense of vast amounts of data. One way that researchers have begun to make high-speed computing more powerful and also more affordable is to build systems that split up workloads among fast, highly parallel graphics processing units (GPUs) and general-purpose central processing units (CPUs).
There is, however, a problem with building these co-processed computing hot rods: A common programming interface for the different GPU models has not been available. Even though the lion's share of GPUs are made by Advanced Micro Devices, Inc. (AMD) and NVIDIA Corp., the differences between the two companies' processors mean that programmers have had to write software to meet the requirements of the particular GPU used by their computers.
Now, this is changing as AMD, NVIDIA and their customers (primarily computer- and game system–makers) throw their support behind a standard way of writing software called the Open Computing Language (OpenCL), which works across both GPU brands. A longer-term goal behind OpenCL is to create a common programming interface that will even let software writers create applications that run both GPUs and CPUs with few modifications, cutting the time and effort required to harness supercomputing power for scientific endeavors.
Researchers at Virginia Polytechnic Institute and State University (Virginia Tech) in Blacksburg, Va., are hoping that OpenCL can help them write software that can run on GPUs made either by AMD or NVIDIA.
From Scientific American
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