Supercomputer Built With 8 GPUs 232
FnH writes "Researchers at the University of Antwerp in Belgium have created a new supercomputer with standard gaming hardware. The system uses four NVIDIA GeForce 9800 GX2 graphics cards, costs less than €4,000 to build, and delivers roughly the same performance as a supercomputer cluster consisting of hundreds of PCs. This new system is used by the ASTRA research group, part of the Vision Lab of the University of Antwerp, to develop new computational methods for tomography. The guys explain the eight NVIDIA GPUs deliver the same performance for their work as more than 300 Intel Core 2 Duo 2.4GHz processors. On a normal desktop PC their tomography tasks would take several weeks but on this NVIDIA-based supercomputer it only takes a couple of hours. The NVIDIA graphics cards do the job very efficiently and consume a lot less power than a supercomputer cluster."
Re-birth of Amiga? (Score:5, Interesting)
Why haven't they started releasing GPU CPUs yet? (Score:3, Interesting)
Re:Why haven't they started releasing GPU CPUs yet (Score:1, Interesting)
Brick of GPUs (Score:5, Interesting)
Between the massive brick of GPUs and the massive CPU heatsink/fan, you can't see the mobo at all.
Vector Computing (Score:2, Interesting)
Re:By what benchmark? (Score:5, Interesting)
Unfortunately, this setup won't work ideally for a lot of other CUDA based applications. For the past 6 months, I had a system with 6 GPUs (actual physical GPUs). This is the system that I showed at CES [ocia.net]. We are easily able to do 8 physical GPUs, and now I've been solely focused on utilizing Tesla.
Given that NVIDIA released the GX2 series, I was not surprised that someone would announce an 8GPU system. I'm surprised it took this long for someone to do it, and almost equally surprised that slashdot took this long to publish any news that is decent in the realm of GPU super computing. I've been cranking out close to 228 billion atom evals. per second in VMD [uiuc.edu] for months now, versus about 4 billion on dual quad core 3.0GHz Xeons.
Re:Not a Supercomputer -- Special purpose hardware (Score:3, Interesting)
Re:By what benchmark? (Score:3, Interesting)
The other critical 40% of my project would have gained absolutely nothing from SIMD and on the Cell would have lost time due to branches. In this case 300 c2d's would far exceed the throughput of 8 GPU's.
Have they profiled it? (Score:4, Interesting)
Re:Wave of the Future? Yes (Score:3, Interesting)
Since when have "vector processors died out"? The "Earth Simulator" for example used the NEC SX-6 CPU, currently the SX-9 is sold. Vector processors never died out and were in use for what they are best at. The GPU and the Cell are no match for either processor, first they both are only fast in single precission mode and much slower when they have to do double precission (the second generation of Cell is better at double precission) and they both have a weak memory subsystem when compared to a true VPU. It is slow and they can only use small memories. As far as I know the Cell can't even chain it's VPUs, something which was standard since the Cray-2 on VPUs.
Re:This is awesome! (Score:1, Interesting)
Re:Re-birth of Amiga? (Score:4, Interesting)
Re:Re-birth of Amiga? (Score:2, Interesting)
Considering how often audio and video gets out of sync on a PC, I will not say they have caught up with the Amiga design.
Another thing to remember is how much Amigas were being used in television production in the past. With an Amiga it was actually possible to sync the entire machine to an external clock source such that the video output could be mixed with another video source.
Syncing the CPU to an external source these days may not be a good idea these days. But syncing audio and video should be a no brainer, it just happens to be tricky to achieve in a modular design.
Another thing is the low latency the Amiga could achieve from input to output. If you moved the mouse while the last few lines of one picture was being sent to the monitor, the position would actually still be updated on the next frame.
We Need a Universal Multicore Processor (Score:3, Interesting)
No doubt about it. In spite of my admittedly negative criticism, I applaud these guys because I think this shows the amazing potential of multicore parallel computing to bringing supercomputing power to the desktop and even to the laptop and the cellphone. However, this potential will not arrive unless we can find a way to design a universal multicore processor architecture that is at home in all possible parallel environments, not just vector parallel systems. IOW, we need a parallel processor that can handle anything we can throw at it with equal ease. Unfortunately, both the industry and academia are pushing the field toward so-called heterogeneous processors, hideous monsters that will be a nightmare to write code for. Check out Nightmare on Core Street [blogspot.com] for good explanation of the multicore crisis and how it can be solved.
Has been done before with PS3s (Score:2, Interesting)
Re:By what benchmark? (Score:3, Interesting)
GPUs on the other hand are far more parallel. The thousands of individual subprocessors can be independently controlled in software and given different tasks.
Re:By what benchmark? (Score:4, Interesting)
In order to utilize this "super computer", your problem has to be refactored in such a way that it can utilize the hardware efficiently. This can be either be fairly easy or incredibly difficult depending on the problem, tool-set available, etc. .
Their benchmark is good for them, but it is most likely meaningless to the general super-computing community. Porting something like LINPACK over and running that as a benchmark however would give a whole lot more insight into what kind of performance boost a typical scientific app might gain from said hardware.
Nice to see someone utilizing this functionality though.
~X~