Nvidia is looking to expand its presence in the high-performance computing market with a second-generation graphics processor that offers 240 graphics processing cores and 1 teraflop of performance.
The graphics company is officially releasing its Tesla 10 series GPU (graphics processing unit) June 16 along with a new 1U (1.75-inch) rack-mount server designed for the increasingly competitive HPC market.
In 2007, Nvidia released the first of its Tesla processors for HPC as the company looked to expand its business beyond its traditional market of discrete graphics and chip sets for PCs. In order to create a community that would develop applications for a GPU-based HPC system, the company also developed a programming language dubbed CUDA (Compute Unified Device Architecture), which allows the GPU to be programmed like an x86 CPU. With the release of the new Tesla GPU, Nvidia is also releasing an early version of CUDA 2.0.
While most HPC is done with traditional microprocessors, Nvidia said it believes the GPU, which can break data apart and solve problems by working in parallel, represents a shift in how to offer more performance at the chip level for solving large, complex problems in fields ranging from financial services to oil and gas exploration.
Amitabh Varshney, a professor of computer science at the University of Maryland, is currently working to create applications that take advantage of HPC systems that use a combination of CPUs and GPUs. He wrote in an email that GPUs have open up new avenues for students and others to think about how write applications that take advantage of the possibilities of parallel computing.
"Over the next few years because of the wide and inexpensive availability of GPUs we might very well see a large number of young parallel programming hobbyists and visual computing enthusiasts who take to GPUs just because it is fun while being challenging," Varshney wrote. "HPC is likely to benefit from a large pool of talented and interested enthusiasts. Another salutary impact of increased affordability of HPC through GPUs is likely to be the broadening of HPC's target areas to a far richer suite of driving applications."
Other IT companies are also using graphics technology to offer better performance for HPC systems and supercomputers. IBM used its own Cell processor as an accelerator in its newly installed Roadrunner supercomputer, while Intel and Advanced Micro Devices are each looking to develop chips that combine CPUs and GPUs on the same silicon die.