The Leading Source for Global News and Information Covering the Ecosystem of High Productivity Computing
July 24, 2008
GeForce GPU runs Folding@home protein simulations 140 times faster than traditional processors
SANTA CLARA, Calif., July 24 -- Stanford University's distributed computing program Folding@home has become a major force in researching cures to life-threatening diseases such as cancer, cystic fibrosis, and Parkinson's disease by combining the computing horsepower of millions of processors to simulate protein folding. The Folding@home project is the latest example in the expanding list of non-gaming applications for graphics processing units (GPU). By running the Folding@home client on an NVIDIA GeForce GPU, protein-folding simulations can be done 140 times faster than on some of today's traditional CPUs.
"The impact of GeForce GPUs on protein folding simulations was immediate and dramatic," said Vijay Pande, associate professor of chemistry, Stanford University and director of the Folding@home project. "Teams that are folding with GeForce GPUs are seeing their production skyrocket. Applying that kind of processing power to Folding@home changes the whole dynamic of the project and could significantly reduce the time it takes to carry out our biomedical research."
The Folding@home project has amassed a large following of computer enthusiasts who compete in teams to churn through as many data units as possible. Their unofficial stats are organized by and displayed at ExtremeOverclocking.com. It took the NVIDIA internal folding team only two weeks to move ahead of 90 percent of all teams, using only 10 machines. After expanding the team to include more GPUs, the NVIDIA team has moved inside the top 0.1 percent of teams in all-time total production in less than a month.
Other folding teams are also seeing their status rise as a result of the NVIDIA Folding@home client.
"We saw the completed work double for our PC Games Hardware Folding team as a result of many team members installing the NVIDIA Folding client," said Carsten Spille, editor at PC Games Hardware. "We are passing many teams every day and we have finally reached our goal of being one of the top 100 folding teams in the world."
Protein Folding
Proteins assemble themselves through a process biologists call "folding." The goal of the Folding@home project is to understand protein folding, misfolding, and related diseases. Folding@home simulates protein folding in order to understand how proteins fold so quickly and reliably and to learn about what happens when proteins do not fold correctly. Diseases such as Alzheimer's disease, cystic fibrosis, BSE (Mad Cow disease), an inherited form of emphysema, and many cancers are believed to result from protein misfolding.
About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in visual computing technologies and the inventor of the GPU, a high-performance processor which generates breathtaking, interactive graphics on workstations, personal computers, game consoles, and mobile devices. NVIDIA serves the entertainment and consumer market with its GeForce products, the professional design and visualization market with its Quadro products, and the high-performance computing market with its Tesla products. NVIDIA is headquartered in Santa Clara, Calif., and has offices throughout Asia, Europe, and the Americas. NVIDIA's inaugural NVISION 08 conference will be held August 25-27, 2008, in San Jose, Calif. For more information, visit http://www.nvidia.com and http://www.nvision2008.com.
-----
Source: NVIDIA
(Digg, Technorati, more)
Petascale Computing: Algorithms and Applications, edited by David A. Bader, is the first book in CRC's Computational Science Series, edited by Horst Simon. Although the book is a collection of papers, Bader has done an excellent job of creating a compilation that holds together and covers a broad topic very well.
Read More...
Cilk++ used in parallelization of the FP-tree algorithm for pattern mining; Istanbul benchmark results posted; and the latest on the NVIDIA Tesla shortage. John West recaps those stories and more in our weekly wrap-up.
Read More...
Last week's International Supercomputing Conference (ISC'09) was a convenient excuse for vendors to announce a raft of new products, but three, in particular, stood out.
Read More...
Jul 06 | The Register | NSA looks to tap into cheap electrical power for new supercomputers. Read more...
Jul 06 | TechRadar | Breaking the exaflops barrier will help keep the nation's nuclear weapons safe. And that's just the start. Read more...
Jul 01 | GenomeWeb Daily News | The popularity of cloud computing in the life sciences community was on full display at April's Bio-IT World conference. Read more...
Jul 01 | Linux Magazine | How can getting to the ocean help with HPC computing? Read more...
Jun 29 | GCN.com | Agency issues RFI for "Ubiquitous High Performance Computing" systems. Read more...
Apr 14 | | Many HPC IT departments are feeling the rising pressure to deliver more capacity computing and performance while trying to reduce the total cost of ownership. This white paper discusses how an environmentally-friendly and open-standards HPC building block based computing system using flexible interconnect options helps address capacity computing needs.
Source: Addison Snell, GM/VP, Tabor Research; sponsored by Dell
Many organizations that could benefit from the use of HPC clusters find that it is complicated to get the systems up and running because of limited IT resources or the complexities of the clusters themselves. Learn how the Intel Cluster Ready program, for which Dell was an original partner, seeks to address this challenge for entry level and mid-range HPC users.
BlueArc's Titan architecture represents an evolutionary step in file servers by creating a hardware-based file system that can scale bandwidth, IOPS, and overall data capacity well beyond conventional software-based devices. With its ability to virtualize a massive storage pool of up to four usable petabytes of tiered storage, Titan can scale with growing data requirements, offering a competitive advantage for businesses, researchers, or other enterprises seeking to better manage data growth while still ensuring optimal performance.
Sun Studio Compilers and Tools and Sun HPC ClusterTools allow you to create high performance parallel applications for OpenSolaris, Solaris and Linux. Sun Studio Express 11/08 includes MPI performance analysis capabilities and full OpenMP 3.0 compiler support. Learn about all this and the latest in Sun HPC ClusterTools 8.1.