NVIDIA awakened the world to the power of computer graphics with the invention of the GPU. Since then, GPUs have been applied to a growing number of the most complex challenges faced by society. For healthcare professionals and their patients, medical imaging technologies running GPUs are delivering safer, faster, higher quality care. Courtesy of NVIDIA

Santa Clara, CA, USA - November 10, 2011

NVIDIA today announced that four leading applications for material-science and biomolecular modeling - LAMMPS, GROMACS, GAMESS, and QMCPACK - have added support for multiple GPU acceleration, enabling them to cut simulation times from days to hours.

Take a glimpse into how scientists and researchers are racing to find answers to important problems that impact our lives. See a snippet of a documentary that depicts how scientific discovery can be accelerated by combining theory and experimentation with computing to fight cancer, prevent heart attacks, and spur new advances in robotic surgery. Watch the full episode here: www.nvidia.com/the-race-for-better-science Courtesy of NVIDIA

As a result, scientists can study larger molecular models for longer time periods with greater accuracy, leading to increased knowledge of the potential impact of drugs and the effectiveness of new materials.

Take a glimpse into how scientists and researchers are racing to find answers to important problems that impact our lives. See a snippet of a documentary that depicts how scientific discovery can be accelerated by combining theory and experimentation with computing to fight cancer, prevent heart attacks, and spur new advances in robotic surgery. Watch the full episode here: www.nvidia.com/the-race-for-better-science Courtesy of NVIDIA

Drug developers could also benefit from shorter discovery times and lower development costs.

Take a glimpse into how scientists and researchers are racing to find answers to important problems that impact our lives. See a snippet of a documentary that depicts how scientific discovery can be accelerated by combining theory and experimentation with computing to fight cancer, prevent heart attacks, and spur new advances in robotic surgery. Watch the full episode here: www.nvidia.com/the-race-for-better-science Courtesy of NVIDIA

The four scientific modeling applications join a growing list of applications - including AMBER, NAMD and TeraChem, among others - that enable university, government and industry researchers to advance research by leveraging the power of GPUs.

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"Wide access to inexpensive, energy efficient supercomputing enabled by GPUs has the potential to accelerate the pace of scientific research," Sumit Gupta, manager of the Tesla business unit at NVIDIA.
"The benefit of this computing power to science is significant, such as enabling researchers to more quickly and accurately simulate biological behavior of protein and drug candidate interactions prior to expensive and time-consuming animal studies and patient trials."

Courtesy of NVIDIA

The four applications are widely used by scientists engaged in using supercomputing to advance modeling in a variety of key areas:

• GAMESS is a quantum chemistry application important in the design of new drugs and materials. It uses computational methods to solve the electronic structure and properties of molecules.

• GROMACS enables the simulation of biomolecular interactions between proteins and drug candidates. It can be used to study protein folding and mis-folding, which is relevant in understanding such diseases as Alzheimer's, Huntington's disease and some forms of cancer.

• LAMMPS is utilized to model, at the atomic scale, soft (biomolecules, polymers) or solid-state (metals, semiconductors) materials.

• QMCPACK simulates the properties of materials, achieving high accuracy and excellent scalability using a continuum quantum Monte Carlo method.


Quotes


"We like to push the envelope as far as we can toward highly scalable efficient code. GPU technology is the most promising way to achieve this goal. Given our association with a DOE laboratory, energy efficiency is equally important, which is another benefit of accelerating quantum chemistry using GPUs."

- Mark Gordon, distinguished professor at Iowa State University's Chemistry Department, director of the Applied Mathematical Sciences Program at AMES Laboratory, project lead for GAMESS

Industry Software Solutions Courtesy of NVIDIA

"GROMACS 4.6 supported by GPUs is expected to accelerate simulation performance 2-3 times faster than previously possible. The greater simulation speed enables research scientists to have deeper insights into the biological behavior of drug candidate and protein receptors involved in diseases."

- Erik Lindahl, professor of Theoretical & Computational Biophysics, KTH Royal Institute, and technology professor of Computational Structural Biology, at Stockholm University's AlbaNova University Center

Industry Software Solutions Courtesy of NVIDIA

"For major workloads using QMCPACK, we're seeing a 3x node-to-node speedup for single-GPU nodes over dual-socket CPU nodes. We're also seeing excellent scaling of this performance for hundreds of GPUs. This allows us to investigate material properties at an unprecedented scale and level of accuracy."

- Jeongnim Kim, R&D scientist at Oak Ridge National Laboratory.

Courtesy of NVIDIA

"Molecular dynamics practitioners are handicapped by well-known timescale limitations: they can't simulate long enough to model many phenomena of interest," said one of the original LAMMPS developers. "Simulation timescales can be extended dramatically by use of large-scale clusters of GPUs."

- Steve Plimpton, distinguished member of technical staff at Sandia National Laboratories

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"The Availability of many computationally efficient GPU nodes locally has allowed us to approach drug design in a new way, giving fresh insights into disease mechanisms. With GPUs, we've been able to run many more simulations with fewer assumptions, creating more realistic models."

- Dr. Michael Kuiper, computational scientist at Victorian Partnership for Advanced Computing

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Biomolecular and material-science researchers interested in a free trial of these new these GPU-accelerated applications can register today for the NVIDIA® Tesla™ MD SimCluster program.

This off-the-shelf integrated cluster solution is fully optimized to simulate large-size models and achieve higher accuracy, while significantly reducing simulation time.


About NVIDIA


NVIDIA (NASDAQ: NVDA) awakened the world to computer graphics when it invented the GPU in 1999.

Today, its processors power a broad range of products from smart phones to supercomputers.

NVIDIA's mobile processors are used in cell phones, tablets and auto infotainment systems.
PC gamers rely on GPUs to enjoy spectacularly immersive worlds.

Professionals use them to create visual effects in movies and design everything from golf clubs to jumbo jets.

NVIDIA’s Santa Clara headquarters. Courtesy of NVIDIA

And researchers utilize GPUs to advance the frontiers of science with high-performance computing.

The company holds more than 2,100 patents worldwide, including ones covering ideas essential to modern computing.

For more information, see www.nvidia.com  


Source: NVIDIA

http://www.nvidia.com/object/newsroom.html  



Chris A. Malachowsky

Co-Founder, NVIDIA Fellow, and Senior Vice President of Research

Chris A. Malachowsky - Co-Founder, NVIDIA Fellow, and Senior Vice President of Research Courtesy of NVIDIA

Chris Malachowsky co-founded NVIDIA in 1993 and has over 30 years of industry experience.

He has been instrumental in managing, defining and driving the company's core technologies as it has grown from a startup to the global leader in visual and parallel computing.

As an executive at NVIDIA, his roles have been diverse, heading numerous functions, including IT, operations, and all facets of the company's product engineering.

He currently is responsible for NVIDIA's world-class research organization chartered with developing the strategic technologies that will help drive the company's future growth and success.

Malachowsky previously held engineering and technical leadership positions at HP and Sun Microsystems.

A recognized authority on integrated-circuit design and methodology, he has authored close to 40 patents.

He holds a BSEE degree from the University of Florida and an MSCS degree from Santa Clara University.
Both schools have honoured Malachowsky with Distinguished Alumnus awards.


Source: NVIDIA

http://www.nvidia.com/object/bio_malachowsky.html  



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