Posted on Monday, November 17 2008 @ 21:21 CET by Thomas De Maesschalck
NVIDIA proudly announced its GPUs are used in the 29th most powerful supercomputing in the world. That may not sound that impressive but it's a huge feat as GPU supercomputing is still in its infancy. The system we're talking about is the Tokyo Institute of Technology's TSUBAMA supercomputer. The TSUBAME features 170 NVIDIA Tesla S1070 1U systems, delivering a peak performance of nearly 170 teraFLOPS and 77.48 teraFLOPS of measured Linpack performance.
"Tokyo Tech is constantly investigating future computing platforms and it had become clear to us that to make the next major leap in performance, TSUBAME had to adopt GPU computing technologies," said Satoshi Matsuoka, division director of the Global Scientific Information and Computing Center at Tokyo Tech. "In testing our key applications, the Tesla GPUs delivered speed-ups that we had never seen before, sometimes even orders of magnitude -- a tremendous competitive boost for our scientists and engineers in reducing their time to solution."
Speaking to the ease of implementation, Matsuoka continued, "The entire upgrade was carried out in 1 week, and the TSUBAME supercomputer remained live throughout. This is an unprecedented feat in top-level supercomputing."
"We are honored to partner with Tokyo Tech -- world famous for their supercomputing expertise and success," said Andy Keane, general manager of the GPU Computing business at NVIDIA. "NVIDIA Tesla breaking into the Top 500 marks a milestone in supercomputing history. The massively parallel GPU is now essential for supercomputing centers worldwide."
The first to achieve Top 500 ranking with an NVIDIA Tesla based GPU cluster, Tokyo Tech, is one of hundreds of distinguished universities and supercomputing centers that have adopted GPU based solutions for research. Other leading centers include the National Center of Supercomputing Applications (NCSA) at the University of Illinois, Rice University, University of Heidelberg, University of Maryland, Max Planck Institute and University of North Carolina.
The Tesla S1070 1U GPU system is based on the NVIDIA CUDA(TM) parallel architecture. This architecture is accessible through an industry standard C language programming environment that allows developers and researchers to tap into the parallel architecture of the GPU more quickly and easily than any other solution shipping today.
