Nvidia has launched the GPU-based Tesla Personal Supercomputer, which delivers the equivalent computing power of a cluster, at a fraction of the price, and in a form factor of a standard desktop workstation.
Priced like a conventional PC workstation, yet delivering 250 times the processing power, researchers now have the horsepower to perform complex, data-intensive computations right at their desk, processing more data faster and cutting time to discovery.
Leading institutions including MIT, the Max Planck Institute, University of Illinois at Urbana-Champaign, Cambridge University and others are already advancing their research using GPU-based personal supercomputers.
At the core of the GPU-based Tesla Personal Supercomputer is the Tesla C1060 GPU Computing Processor, which is based on the Nvidia Cuda parallel computing architecture. Cuda enables developers and researchers to harness the massively parallel computational power of Tesla through industry standard C.
