WASHINGTON, D.C. – Two U.S. Department of Energy (DOE) National Laboratories were recently awarded the 2018 Association for Computing Machinery’s (ACM’s) Gordon Bell Prize. A team co-led by Oak Ridge National Laboratory (ORNL) was recognized for their paper “Attacking the Opioid Epidemic: Determining the Epistatic and Pleiotropic Genetic Architectures for Chronic Pain and Opioid Addiction,” and a team from Lawrence Berkeley National Laboratory was recognized for their paper “Exascale Deep Learning for Climate Analytics.”

“The Gordon Bell Prize exemplifies why supercomputing is critical to DOE's core mission, and why its applications are so important,” said U.S. Secretary of Energy Rick Perry. “DOE’s national laboratories are at the forefront of this revolutionary technology. From problem-solving the opioid epidemic, to improving the care of our nation's veterans, to advanced climate modeling, we are beginning to see some of the truly incredible work accomplished by the world’s fastest computers.”

The team at ORNL was derived from a joint Department of Energy-Department of Veterans Affairs (VA) Memorandum of Agreement focused on advancing precision medicine and technology innovation initiatives to improve the healthcare of the nation’s veterans. Joint programs, including MVP-CHAMPION and ACTIV, build on DOE’s high-performance computing, artificial intelligence, and big data analytics capabilities to push development of DOE technologies in key areas while advancing the VA mission objectives of analyzing Veterans health and genomic data and improving corresponding care and treatment.



“In Veterans Affairs we are committed to using innovative means to attack our biggest issues,” said VA Secretary Robert Wilkie. “This award reflects the hard work of numerous people in our efforts to address issues related to chronic pain and opioid addiction. We will continue to seek out new ways to help our Veterans and, by extension, our fellow American citizens.”

The ORNL-led team developed a new “CoMet” algorithm that allows supercomputers to process vast amounts of genetic data and identify genes that may be more susceptible to pain and opioid addiction—as well as promising treatments. By running the ORNL team’s algorithm, supercomputers were able to successfully process genetic data at a magnitude that is 300,000 times greater than the latest state-of-the-art approaches.

The second winning team, based at Berkeley Lab, was recognized for their work in applying high-performance computing to climate modeling and analytics. Applying exascale computing to climate modeling allows climate scientists to configure and run high-fidelity simulations under a range of different climate change scenarios. The LBNL team paper proposed an innovative blend of hardware and software solutions. These included a novel architecture as well as a number of system-level innovations to enable the largest graphics processing units (GPU)-based HPC systems in the world to process vast amounts of weather-related data. Their application represents the largest successful high performance computer scaling of a deep learning application to date.

The ACM Gordon Bell Prize tracks the progress of parallel computing and rewards innovation in applying high performance computing to challenges in science, engineering, and large-scale data analytics.

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