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SDSC Houses Novel Metabolomics Data Repository

September 14, 2021 — How is the “normal” resting heart rate determined? How does the American Diabetes Association establish the “normal” fasting glucose value? Understanding these “normal” ranges for metabolism is complex, especially because the human body may contain tens of thousands of metabolites at any one time; each individual molecule could be tied to […]

SDSC Part of New NSF Project Supporting Transboundary Aquifer Resiliency

August 11, 2021 — Transboundary aquifers, which are deep subsurface water sources shared by multiple countries, have long been a critical source of water for communities along the borders of the U.S. and Mexico. Recent decline in water levels and quality – coupled with increased use – provoked concern regarding long-term sustainability of several transboundary aquifers […]

SDSC Team Awarded Funding for NSF GO FAIR Symposium

Aug. 10, 2021 — The San Diego Supercomputer Center’s (SDSC) Research Data Services (RDS) Chief Strategist Melissa Cragin and Division Director Christine Kirkpatrick were recently awarded a grant by the National Science Foundation to fund a GO FAIR symposium in the next several months. The production of Findable, Accessible, Interoperable and Reusable (FAIR) data and […]

SDSC Picks Habana AI Training and Inference Chips for Voyager HPC System

The San Diego Supercomputer Center has selected Habana Labs’ AI training and inference accelerators for SDSC’s Voyager supercomputer, scheduled to be in service this fall. Habana said the HPC system, housed at the University of California, San Diego, will utilize Habana’s interconnectivity technology to scale AI training capacity with 336 Habana Gaudi training processors, which […]

XSEDE-Allocated Supercomputers, Comet and Stampede2, Accelerate Alzheimer’s Research

By Kimberly Mann Bruch, San Diego Supercomputer Center Communications Since 2009, Daniel Tward and his collaborators have analyzed more than 47,000 images of human brains via MRI Cloud — a gateway created to collect and share quantitative information from human brain images, including subtle changes in shape and cortical thickness. The latter was the topic of […]

MIT Researchers Develop Neural Networks for Computational Chemistry Using SDSC, PSC Supercomputers

Even though computational chemistry represents a challenging arena for machine learning, a team of researchers from the Massachusetts Institute of Technology (MIT) may have made it easier. Using Comet at the San Diego Supercomputer Center at UC San Diego and Bridges at the Pittsburgh Supercomputing Center, they succeeded in developing an artificial intelligence (AI) approach to detect electron correlation – the interaction between a system’s electrons – which is vital but expensive to calculate in quantum chemistry.