- NVIDIA GRID
- NVIDIA VCA
- NVIDIA DRIVE
- 3D Vision
- About NVIDIA
Users Harness the Power of NVIDIA Tesla GPUs for Enterprise Computing on Windows HPC Server 2008
For further information, contact:
FOR IMMEDIATE RELEASE:
SANTA CLARA, Calif.—Sep. 28, 2009— NVIDIA today announced work with Microsoft to promote NVIDIA® Tesla™ graphics processing units (GPUs) for high performance parallel computing using the Windows HPC Server 2008 operating system.
“The coupling of GPUs and CPUs illustrates the enormous power and opportunity of multicore co-processing,” said Dan Reed, corporate vice president of Extreme Computing at Microsoft. “NVIDIA’s work with Microsoft and the Windows HPC Server platform, is helping enable scientists and researchers in many fields achieve supercomputer performance on diverse applications.”
NVIDIA Research developed several GPU-enabled applications on the Windows HPC Server 2008 platform, such as a ray tracing application that can be used for advanced photo-realistic modeling of automobiles. Related to this, NVIDIA worked with Microsoft Research to install a large Tesla GPU computing cluster and is studying applications that are optimized for the GPU.
In addition, a whole range of enterprise applications – such as data mining, machine learning and business intelligence, as well as scientific applications like molecular dynamics, financial computing and seismic processing – are taking advantage of the massively parallel CUDA™ architecture on which NVIDIA’s GPUs are based to achieve higher levels of productivity.
The CUDA architecture enables developers to use the CPU and the GPU together in a co-processing model. Compute-intensive sections of an application use the parallel computing capabilities of the GPU, while the sequential part of an application’s code runs on the CPU.
“The combination of GPUs and the Windows platform has been a great benefit to our VMD (Visual Molecular Dynamics) user community, bringing advanced molecular visualization and analysis capabilities to thousands of users,” said John Stone, senior research programmer at the University of Illinois Urbana-Champaign. “As we move toward even larger biomolecular structures, GPUs will become increasingly important as they bring even more computational power to bear on what will be highly parallelizable computational problems.”
“The scientific community was one of the first to realize the potential of the GPU to transform its work, observing speedups ranging from 20 to 200 times while using a range of compute-intensive applications,” said Andy Keane, general manager of NVIDIA’s Tesla business. “Researchers are increasingly using Windows on workstations and in data centers due to strong development tools like Microsoft Visual Studio, its ease of system management and its lower total cost of ownership.”
NVIDIA Tesla high-performance GPU computing products support Windows XP and Windows Vista in the workstation and Windows Server 2003 and Windows Server 2008 in the data center. Tesla C1060 and S1070 GPU computing products are available from most major system vendors including Cray, Dell, HP and Lenovo.
NVIDIA (Nasdaq: NVDA) awakened the world to the power of computer graphics when it invented the graphics processing unit (GPU) in 1999. Since then, it has consistently set new standards in visual computing with breathtaking, interactive graphics available on devices ranging from portable media players to notebooks to workstations. NVIDIA’s expertise in programmable GPUs has led to breakthroughs in parallel processing which make supercomputing inexpensive and widely accessible. Fortune magazine has ranked NVIDIA #1 in innovation in the semiconductor industry for two years in a row. For more information, see www.nvidia.com.
Certain statements in this press release including, but not limited to, statements as to: the benefits, features, impact, performance and capabilities of NVIDIA Tesla GPUs and CUDA architecture; and the benefits of multicore coprocessing; are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: development of more efficient or faster technology; design, manufacturing or software defects; the impact of technological development and competition; changes in consumer preferences and demands; customer adoption of different standards or our competitor's products; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems as well as other factors detailed from time to time in the reports NVIDIA files with the Securities and Exchange Commission including its Form 10-Q for the fiscal period ended July 26, 2009. Copies of reports filed with the SEC are posted on our website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.
# # #
© 2009 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, Tesla, and CUDA, are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. Other company and product names may be trademarks of the respective companies with which they are associated. Features, pricing, availability, and specifications are subject to change without notice.