LLNL

Lawrence Livermore National Laboratory has installed a new high-performance computing (HPC) cluster with enough memory and storage for data-intensive COVID-19 research and pandemic response.

Funded by the federal Coronavirus Aid, Relief and Economic Security (CARES) Act, the “big memory” cluster, called Mammoth, will be used for genomics analysis, nontraditional HPC simulations, and graph analytics required by scientists working on COVID-19, including the development of antiviral drugs and designer antibodies.

“The ability of large-memory systems to integrate genomic analysis with large-scale machine learning for predictive modeling of therapeutic response will be important for accelerating the development of effective new therapeutics,” said Jim Brase, the lab’s deputy associate director for computing.

“Mammoth will be integral for developing new tools to combat COVID-19, but also for fast response in a future pandemic,” Brase said.

Mammoth includes 64 nodes, each with two 64-core CPUs, features high-memory bandwidth and providing two terabytes of random-access memory and nearly four terabytes of nonvolatile memory. The extra memory is critical for COVID-19 researchers, who must sift through massive databases of information.

“It is exciting to see a direct connection between technology and the science being done to improve or even save lives,” said Dan McNamara, senior vice president with Advanced Micro Devices, a partner in Mammoth with LLNL. “AMD is proud to support the vital research being done by the team at LLNL with Mammoth in conjunction with our technology partners at Supermicro and Cornelis Networks.”

LLNL researchers have begun applying Mammoth to the genome of the SARS-CoV-2 virus that causes COVID-19, using the computing cluster to analyze how the virus evolves and simulating how its structure changes when they introduce mutations.

Mammoth is helping reduce the time it takes to perform some types of genomic analysis from a few days to a few hours, according to the researchers. Mammoth’s memory resources and numerous cores are also aiding in the design of modified antibodies.