NVIDIA has announced that it will be a founding member of Stanford University’s new Pervasive Parallelism Lab [PPL]. The PPL’s charter is to develop new techniques, tools and training materials to allow software engineers to harness the parallelism of multi-processor systems [including multi-core].
Parallel programming is perhaps the largest problem in computer science today and is the major obstacle to the continued scaling of computing performance that has fueled the computing industry, and several related industries, for the last 40 years,” says Bill Dally, chair of the computer science department at Stanford.
This move complements NVIDIA’s push into traditional high performance computing markets with their CUDA development tools.
NVIDIA has been tackling parallel computing challenges since its founding and, as a result, the GPU has evolved into an incredibly powerful processor, capable of running thousands upon thousands of concurrent operations,” said David Kirk, chief scientist at NVIDIA. “We applaud, and are proud to be a part of, Stanford University’s formation of the PPL and its mission to push the software industry to expose the inherent parallelism in today’s computers.”
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