NDAs Re: [Beowulf] Nvidia, cuda, tesla and... where's my
double floating point?
james.p.lux at jpl.nasa.gov
Tue Jun 17 07:01:16 PDT 2008
Quoting Linus Harling <linus at ussarna.se>, on Mon 16 Jun 2008 04:31:56 PM PDT:
> Vincent Diepeveen skrev:
>> Then instead of a $200 pci-e card, we needed to buy expensive Tesla's
>> for that, without getting
>> very relevant indepth technical information on how to program for that
>> type of hardware.
>> The few trying on those Tesla's, though they won't ever post this as
>> their job is fulltime GPU programming,
>> report so far very dissappointing numbers for applications that really
>> matter for our nations.
> Tomography is kind of important to a lot of people:
> But of course, that was done with regular $500 cards, not Teslas.
Mind you, if you go and get a tomographic scan today, they already use
fast hardware to do it. Only researchers on limited budgets tolerate
taking days to reduce the data on a desktop PC. And, while the concept
of doing faster processing with a <10KEuro box is attractive in that
environment, I suspect it's a long way from being commercially viable
in that role.
The current tomographic technology (e.g. GE Lightspeed) is pretty
impressive. They slide you in, and 10-15 seconds later, there's 3 d
rendered models and slices on the screen. The equipment is pretty
hassle free, the UI straightforward from what I could see, etc.
And, of course, people are willing (currently) to pay many millions
for a machine to do this. I suspect that the other costs of running a
CT scanner (both capital and operating) overwhelm the cost of the
computing power, so going from a $100K box to a $20K box is a drop in
the bucket. When you're talking MRI, for instance, there's the cost
of the liquid helium for the magnets.
That's a long way from a bunch of grad students racking up a bunch of PCs.
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