SC22, Dallas, TX. November 14, 2022— SambaNova Systems is delivering its SambaNova’s DataScale® system to the U.S. Department of Energy’s Argonne National Laboratory to provide a new resource for accelerating AI for science workloads, including large-scale imaging data and large language models.
DataScale is a fully integrated hardware-software system that enables organizations to reimagine their approach to AI.
“With the rollout of Argonne’s SambaNova systems, we’re seeing scientists use novel AI architectures for pioneering research in areas ranging from climate predictions to neutrino physics,” said Rick Stevens, Argonne’s associate laboratory director for Computing, Environment and Life Sciences. “The new SambaNova system will help boost AI-driven research including our efforts to use deep learning to predict how tumors respond to various drug combinations and, in general, foundation AI models for science.”
“The new capabilities and increased memory capacity of SambaNova’s DataScale will open the door to a wider range of AI for science applications involving large AI models and massive datasets,” added Venkat Vishwanath, data science team lead at the Argonne Leadership Computing Facility (ALCF), a DOE Office of Science user facility. “We look forward to running large-scale AI models on the new system to accelerate insights into the growing deluge of scientific data being produced by simulations and experiments, including the high-resolution imaging data being generated at DOE light sources.”
The new DataScale system will be made available to the scientific community via the ALCF AI Testbed, a growing collection of some of the world’s most advanced AI accelerators. The ALCF AI Testbed is designed to enable researchers to explore deep learning and Foundation Model workloads to advance AI for science. The ALCF’s AI platforms complement the facility’s current and next-generation supercomputers to provide a state-of-the-art environment that supports research at the intersection of AI, big data, and high-performance computing.
“The multi-year deal being announced today is an expansion of our current partnership with Argonne National Laboratory,” said Marshall Choy, SVP of Product at SambaNova Systems. “The partnership showcases Argonne’s adoption of a multi-rack SambaNova system and joint efforts on implementing challenging foundation model and deep learning workloads. For scientific research organizations, this means new experiments and discoveries with the potential to change the world.”
Researchers at Argonne have been using SambaNova’s previous generation system for a wide range of studies, including developing surrogate models to improve weather forecasting accuracy, speeding up computational fluid dynamics simulations for engine research, and processing high resolution image datasets to accelerate experimental discoveries. The science use cases explored to date include:
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Researchers interested in using the AI Testbed’s SambaNova DataScale system can submit project proposals via the ALCF’s Director’s Discretionary program. https://www.alcf.anl.gov/alcf-ai-testbed
About Argonne National Laboratory
Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science.
About The U.S. Department of Energy’s Office of Science
The U.S. Department of Energy’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science.
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