NDAs Re: [Beowulf] Nvidia, cuda, tesla and... where's my double floating point?

[Jim Lux]

Quoting Linus Harling <linus at ussarna.se>, on Mon 16 Jun 2008 04:31:56 PM PDT:

> Vincent Diepeveen skrev:
> <snip>
>>
>> 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.
> </snip>
>
> Tomography is kind of important to a lot of people:
>
> http://tech.slashdot.org/tech/08/05/31/1633214.shtml
> http://www.dvhardware.net/article27538.html
> http://fastra.ua.ac.be/en/index.html
>
> 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.