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High-performance computing in fields such as geosciences, molecular biology, and medical diagnostics enable discoveries that transform billions of lives every day. Universities, research institutions, and companies in these and other related fields face a daunting challenge: As their simulation models become exponentially complex, so does their need for vast computational resources.
Nvidia took a giant step in meeting this challenge with the recent announcement of a new class of processors based on a new graphics processing unit (GPU). Under the Tesla brand, Nvidia will offer a family of GPU computing products that will place the power previously available only from supercomputers in the hands of scientists and engineers, thereby transforming today's workstations into "personal supercomputers."
"Today's science is no longer confined to the laboratory; scientists employ computer simulations before a single physical experiment is performed. This fundamental transition to computational methods is forging a new path for discoveries in science and engineering," says Jen-Hsun Huang, president and CEO of Nvidia. "Tesla dramatically reduces computation times, in some cases from weeks to hours."
The Tesla family of GPU computing solutions spans from PCs to large-scale server clusters and includes three new products. Tesla GPU Computing Processor is a dedicated computing board that scales to multiple Tesla GPUs inside a single PC or workstation. The Tesla GPU features 128 parallel processors and delivers up to 518 gigaflops of parallel computation. The GPU computing processor can be used in existing systems, partnered with high-performance CPUs.
The Tesla Deskside Supercomputer is a scalable computing system that includes two Nvidia Tesla GPUs ...