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GPU goes supercomputer co-processor
Written by Daniel   
Thursday, 05 April 2007 10:06

New beer in wine bottles: NVIDIA to rebrand G80 as supercomputer chip

By Jon Stokes | Published: April 04, 2007 - 11:35PM CT
ARS Technica

If you've been following my coverage of the high performance computing (HPC) market—especially my coverage of the emerging market for commodity data-parallel coprocessors that are repurposed for use in HPC clusters—then know this: NVIDIA hates my line on all this stuff, and they haven't been shy about letting me know it. Now, I reveal this not in order to be catty, but to provide some context for a new rumor (courtesy of The Street) that NVIDIA will soon launch a separate "GPU computing" brand dedicated to selling the G80 to businesses as a general-purpose data-parallel coprocessor. Knowing that NVIDIA dislikes my GPU-as-coprocessor coverage, and knowing what they don't like about it, is key to understanding why they're launching a whole separate brand and product line around an existing GPU part.

First, let's contrast my typical take on the GPU in general, whether from AMD/ATI or NVIDIA, as a data-parallel coprocessor with the message that NVIDIA has been trying to attach to the G80 via their CUDA initiative:

Me: Anybody's GPU, whether it's from NVIDIA or AMD/ATI, is a big, hot, power-hungry, beast of a coprocessor that's designed to do one thing extremely well: real-time 3D rendering for games. In fact, we can be even more specific and call a GPU a "Microsoft DirectX toaster." These same DirectX toasters also just happen to offer significant speedups vs. a regular microprocessor for certain types of data-parallel workloads that are important in HPC.

NVIDIA: The G80 is a general-purpose data-parallel coprocessor that gives top-notch performance in all kinds of applications, including computational genomics, quantitative financial analysis, seismic analysis, medical imaging, simulations... and 3D games.... More

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