Portland, Ore. (Nov. 16, 2009) - The U.S. Department of Energy's (DOE) Argonne National Laboratory has been awarded the HPCwire's Readers' Choice Award for Best Application of Green Computing. The award was presented by Tomas Tabor, publisher of HPCwire, at the annual Supercomputing Conference (SC09), being held in Portland, Ore.

"This award, which represents a partnership between the HPCwire global readership and our publishing team, is a salute from the global HPC community," said Tabor. "Being selected as an award recipient means that you are at the top of mind of HPCwire readers, editors and luminaries in the field. I'd like to congratulate Argonne National Laboratory for being selected by our readers for a 2009 award."

"We are honored to be recognized by the high performance computing community," said Pete Beckman, director of Argonne's Leadership Computing Facility (ALCF). "At Argonne, we are continually looking for ways to be more energy efficient and environmentally friendly."

The ALCF is home to Intrepid, an energy-efficient IBM Blue Gene/P supercomputer, which uses about one-third as much electricity as a comparable supercomputer. Argonne is able to achieve such savings in energy through a variety of innovative operational techniques, including methods employed to cool the supercomputer - a process that normally requires more electricity than powering the machine itself.

For example, the ALCF saves up to tens of thousands of dollars a month in electricity costs during the winter months by using the Chicago area's frigid temperatures to chill the water used to cool Intrepid, alleviating the need to run power hungry centrifugal chillers. In addition, ALCF is working with IBM to use the warmest possible water temperature necessary to effectively cool the computer systems, leading to even greater savings and reduced environmental impact.

Argonne compute and storage systems have "smart power" management functionality that allows them to turn off or throttle back the power consumption. Argonne is working on strategies to get maximum benefit from these capabilities. For instance correlating power consumption to the jobs and then developing algorithms that might run power hungry jobs at night when electricity is cheaper.

Computing awardMedia Contact

Eleanor Taylor