MIT Artificial Vision Researchers Assemble 16-GPU Machine

lindik writes "As part of their research efforts aimed at building real-time human-level artificial vision systems inspired by the brain, MIT graduate student Nicolas Pinto and principal investigators David Cox (Rowland Institute at Harvard) and James DiCarlo (McGovern Institute for Brain Research at MIT) recently assembled an impressive 16-GPU 'monster' composed of 8x9800gx2s donated by NVIDIA. The high-throughput method they promote can also use other ubiquitous technologies like IBM's Cell Broadband Engine processor (included in Sony's Playstation 3) or Amazon's Elastic Cloud Computing services. Interestingly, the team is also involved in the PetaVision project on the Roadrunner, the world's fastest supercomputer."

Comments

Re:Just how specialized is GPU hardware?

[moteyalpha]

I have been using my own GPU to do this very same thing by automatically converting images to vertex format and use the GPU to scale, shade, etc and in this way I can have a shape recognition by simply measuring the closest match on the frame buffer. There are more complex ways to use the GPU to do pseudo computation in parallel, I still think that a commonly available CAM or near CAM would increase neural like computations by being essentially a completely parallel process. It would be better to allow more people to experiment with the methods because the greatest gain and cost is the software itself and specialized hardware for a single purpose allows better profit but limits innovation.

Fascinating

[AlienIntelligence]

I think this part of the computing timeline is going to be
one that is well remembered. I know I find it fascinating.

This is a classic moment when tech takes the branch that
was unexpected. GPGPU computing will soon
reach ubiquity but for right now it's the fledgling that is being
grown in the wild.

Of course I'm not earmarking this one particular project
as the start point but this year has gotten 'GPU this' and
'GPGPU that' start up events all over it. Some even said
in 2007, that it would be a buzzword in 08.

And of course there's nothing like new tech to bring out
a naysayer.

Folding@home released their second generation
GPU client in April 08. While retiring the GPU1 core in
June of this year.

I know I enjoy throwing spare GPU cycles to a distributed
cause and whenever I catch sight of the icon for the GPU
client it brings the back the nostalgia of distributed clients
of the past. [Near the bottom].

I think I was with United Devices the longest.
And the Grid.

Now we are getting a chance to see GPU supercomputing
installations from IBM and this one from MIT.
Soon those will be littering the Top 500 list.

I also look forward most to the peaceful endeavors the new
processing power will be used for... weather analysis,
drug creation, and disease studies.

Oh yes, I realize places like the infamous Sandia will be using
the GPU to rev up atom splitting. But maybe if they keep their
bombs IN the GPU it'll lessen the chances of seeing rampant
proliferation again.

Ok, well enough of my musings over a GPU.

-AI