[Beowulf] NVIDIA GPUs, CUDA, MD5, and "hobbyists"

Peter St. John peter.st.john at gmail.com
Thu Jun 19 09:52:26 PDT 2008


I dug up this pdf from Nvidia:
http://www.nvidia.com/docs/IO/43395/tesla_product_overview_dec.pdf
Since I can't imagine coding a graphics card while it serves my X :-) I
supposed one might put the PCIE card in a box with a cheap SVGA for the
least-cost  CUDA experiment (one GPU, 128 "thread processors" per GPU). The
deskside is 2 GPU with 3 GB, the rackable is 4 GPU with 6 GB; they have PCIE
adapter cards to talk to your workstation.

I think one plan might be like the GraPE (Gravity Pipe); maybe one of the
rackables alternating with a CPU MB acting as net host and fileserver, so
each (2-board) node has 4 GPU for array computing.
Peter

P.S. incidentally, while I was browsing Nvidia, I spec'd out a fantasy
gaming rig. $23K, 256GB of solid state "disk", 3x 1GB video cards, 180W just
to liquid-cool the CPU :-) Maybe next year.

On 6/19/08, John Hearns <john.hearns at streamline-computing.com> wrote:
>
> On Wed, 2008-06-18 at 16:31 -0700, Jon Forrest wrote:
>
> > Kilian CAVALOTTI wrote:
>
> > I'm glad you mentioned this. I've read through much of the information
> > on their web site and I still don't understand the usage model for
> > CUDA. By that I mean, on a desktop machine, are you supposed to have
> > 2 graphics cards, 1 for running CUDA code and one for regular
> > graphics? If you only need 1 card for both, how do you avoid the
> > problem you mentioned, which was also mentioned in the documentation?
>
> Actually, I should imagine Kilian is referring to something else,
> not the inbuilt timeout which is in the documentation. But I can't speak
> for im.
>
>
>
>
> > Or, if you have a compute node that will sit in a dark room,
> > you aren't going to be running an X server at all, so you won't
> > have to worry about anything hanging?
>
>
> I don't work for Nvidia, so I can't say!
> But the usage model is as you say - you can prototype applications which
> will run for a short time on the desktop machine, but long runs are
> meant to be done on a dedicated back-end machine.
> If you want a totally desk-side solution, they sell a companion box
> which goes alongside and attaches via a ribbon cable. I guess the art
> here is finding a motherboard with the right number and type of
> PCI-express slots to take both the companion box and a decent graphics
> card for X use.
>
>
>
> >
> > I'm planning on starting a pilot program to get the
> > chemists in my department to use CUDA, but I'm waiting
> > for V2 of the SDK to come out.
> >
>
>
> Why wait? The hardware will be the same, and you can dip your toe in the
> water now.
>
>
>
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