NVIDIA GPUs to Accelerate Gaussian Quantum Chemistry Application

Published: Sep 7th 2011, 15:20 GMT

NVIDIA GPUs to Accelerate Gaussian Quantum Chemistry Application | GPU Science
A bit to late but anyway … NVIDIA, Gaussian, PGI Announce Collaboration to Reduce the Time and Cost Required to Run Complex Calculations!
SANTA CLARA, CA — 08/29/2011 NVIDIA announced plans with Gaussian, Inc., and The Portland Group (PGI) to develop a future GPU-accelerated release of Gaussian, the world’s leading software application for quantum chemistry.

The Gaussian series of electronic-structure modeling programs is widely used worldwide by chemists, chemical engineers, biochemists, physicists, and others working on molecular-level chemical research. It enables researchers to study and predict the properties of molecules and reactions under a wide range of conditions, especially those that are difficult or impossible to observe experimentally.

By adding support for high-performance NVIDIA® Tesla™ GPUs and compilers from PGI in a future release of Gaussian software, researchers will have a powerful, more efficient tool to help reduce the cost and time required for running complex, data-intensive calculations. The GPU-accelerated version of Gaussian will be developed by a three-way collaboration among NVIDIA, Gaussian and PGI.

“Calculations using Gaussian are limited primarily by the available computing resources,” said Dr. Michael Frisch, president of Gaussian, Inc. ”By coordinating the development of hardware, compiler technology and application software among the three companies, the new application will bring the speed and cost-effectiveness of GPUs to the challenging problems and applications that Gaussian’s customers need to address.”

NVIDIA Tesla GPUs, based on the NVIDIA® CUDA parallel computing architecture, deliver transformative performance increases across a wide range of fields, including image and video processing, computational biology and chemistry, fluid dynamics simulation, image reconstruction, seismic analysis, and more. Designed specifically for high performance computing (HPC) environments, Tesla GPUs power three of the world’s top five supercomputers.

“NVIDIA customers use GPU acceleration to push the boundaries in life sciences, and have been requesting a GPU-accelerated version of Gaussian,” said Andrew Cresci, general manager of NVIDIA’s Strategic Alliances Group. ”Adding Gaussian acceleration support with NVIDIA GPUs will enable computational chemists and engineers to tackle significant scientific problems more efficiently and cost-effectively than with competitive solutions. The potential jump in productivity is huge.”

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