Will Your Next Shampoo Be Developed on GPUs?

Temple University Researchers Help Procter Two NVIDIA Tesla GPUs Beat 1024 CPU BlueGene/L Cluster

SANTA CLARA, CA -- Improving the cleaning power of shampoos and liquid detergents and making them more environmentally friendly is as much a computer problem as it is a balance of chemicals. By harnessing the parallel processing power of NVIDIA(R) Tesla(TM) GPUs, researchers at Temple University are developing a computer simulation model which provides companies like Procter and Gamble with a fast, cost effective and accurate tool for research and development of surfactant molecules.

Surfactants have many uses; for example they provide the cleaning capacity and texture of shampoos, laundry detergents, and many other cleaning products. Their job is to attach themselves to dirt and make it mix with water, and their effectiveness in this process determines their ability to clean. The process of finding new, better surfactants and testing their effectiveness in laboratories is time consuming and costly.

"The computer models needed to accurately simulate surfactant properties are extremely demanding in terms of computational power," said Axel Kohlmeyer of the Institute for Computational Molecular Science at Temple University. "We discovered that by adding just two NVIDIA Tesla C1060 GPUs, each node in our newest cluster can do 16 times more work, and thus multiplies our local compute capacity far beyond what we could previously get through the national supercomputing centers."

"To put this into context, we can run a single GPU-optimized molecular dynamics simulation on two Tesla GPUs as fast as we can on 128 CPU cores of a Cray XT3 supercomputer or on 1024 CPUs of an IBM BlueGene/L machine with conventional software," continues Dr. Kohlmeyer. "With the NVIDIA Tesla GPU-based solution, we now have a more powerful, cost-effective solution that will enable us to advance critical research at a much faster pace. We're moving rapidly ahead to deploy a larger Tesla GPU cluster at Temple, which will give another huge boost to our work."

The Temple researchers are using GPU-accelerated HOOMD (Highly Optimized Object Oriented Molecular Dynamics) simulation software, written by researchers at the Department of Energy's Ames Laboratory to leverage the NVIDIA GPUs.

In addition to deploying a small local GPU cluster, the university team will also look to scale its work using the NCSA Lincoln cluster, where the computational output has been boosted to 47 TeraFLOPS through the addition of Tesla S1070 1U GPU systems.

For more information:

Video of the Temple University team discussing their work in surfactant research Molecular dynamics using GPUs Institute for Computational Molecular Science at Temple University The HOOMD application from Ames Lab

NCSA Supercomputer

About NVIDIA

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. 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 effect of NVIDIA Tesla GPUs on Lowry Digital's restoration process 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 April 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.

Copyright 2010 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, Tesla, CUDA, GeForce and Quadro are trademarks 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.

For more information, contact: Andrew Humber NVIDIA Corporation (408) 416 7943 ahumber@nvidia.com

SOURCE: NVIDIA

mailto:ahumber@nvidia.com

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