Notes from NVIDIA's ISC'10 briefing

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During ISC’10 NVIDIA hosted a special session of briefings that our man Rich attended and wrote about. NVIDIA has put Andy Keane’s slides from that session online, and I was just trolling through it. Here are a few of the items that I noted

nVidia logoIn 2008 NVIDIA’s R&D budget was close to $900M — by way of comparison, Cray spent $51.77M on R&D in the same year, and SGI spent $13.8M. I know: NVIDIA is still mostly a consumer products company, so the comparisons aren’t great, but still. Intel and AMD spent $5.722B and $1.848B, respectively, in the same year.

7 releases in 3 years — a slide in Andy’s deck highlights the fact that CUDA (and its associated tools) have had 7 releases in 3 years. The context is that this is a good thing, and it probably is, to a point. But NVIDIA cannot continue that pace and still grow the adoption base. At some point the churn in the tools drives away developers.

Community code ports — there is a fairly large body of community science codes that are now ported to CUDA. The deck shows about 25, with apps from WRF to AMBER.

5 PFLOPS — Andy showed the slide that NVIDIA has been talking to recently that shows a notional pure x86-based 5 PLFOPS machine at 20MW, and then a GPU-enabled hybrid machine at 10MW for the same theoretical peak. And we are shooting for an EFLOPS in 20MW by decade end?


  1. anonymous says

    “…At some point the churn in the tools drives away developers…”

    Perhaps if you are over 40. The younger generation feeds on agile development and HPC would be better if it did too.

  2. John West says

    @Anonymous: I disagree pretty strongly for at least some areas of the HPC ecosystem. There is a qualitative difference in the workflow and tools people need when their applications support decisions that directly impact life and limb, as you find in high end HPC calculations related to national defense, homeland security, safety, drug design, and so on. Major companies and research organizations build out programs of investment that span decades, and some stability, or at least predictability, in the toolset is required.