Hardware maker Nvidia has announced thier new computer that has the power of a cluster of computers at a small fraction of the cost.

Nvidia, working with several partners, Dell, Lenovo, Asus, Western Scientific, and others, has developed the Tesla Personal Supercomputer, using the graphics processing unit based on Nvidia’s Cuda parallel computing architecture.

Burton Smith, a technical fellow at Microsoft stated while there have been claims of desktop supercomputers in the past, “this time it’s for real,”

Nvidia representiatives say computers using the Tesla C1060 GPU processor will have something like 250 times the processing power of a typical PC workstation, enabling researchers to run complicated simulations, experiments and number crunching processes without the need for a supercomputer.

This so-called "personal supercomputer" will incorporate anywhere from two to four Tesla C1060 processors, which are made up of 240 stream processing cores.

A computers cluster can run a many times the cost of one of the Tesla-powered workstations. The Tesla C1060 card, available on computers Tuesday, will sell for $1,699, with desktop computer systems including the card selling for less than $9,995, said Andrew Humber, an Nvidia spokesman. The systems would run at a processing speed of four teraflops, or four trillion floating point operations per second.

"This represents phenomenal price/performance for computational researchers who have typically had to compete for time on expensive and power-hungry clusters," the Nvidia spokesperson said in an e-mail.

Several institutions, including the University of Illinois at Urbana-Champaign and Cambridge University,and the Max Planck Institute are already using GPU-based personal supercomputers.

“GPU based systems enable us to run life science codes in minutes rather than the hours it took earlier,” Jack Collins, manager of scientific computing and program development at SAIC-Frederick’s Advanced Biomedical Computing Center in Frederick, Maryland, said in a statement. "This speed-up has the ability to accelerate the discovery of potentially life-saving anti-cancer drugs.”

While most HPC clusters and supercomputers are powered by conventional CPUs, Nvidia is betting that its general-purpose GPUs can offer the types of performance that scientists, researchers and other workers in the High Powered Computer market need now to run these types of massive workloads.

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