Upgrades for LLNL supercomputer from AMD, Penguin Computing aid COVID-19 research

To assist in the COVID-19 research effort, Lawrence Livermore National Laboratory, Penguin Computing and AMD have reached an agreement to upgrade the Lab’s unclassified, Penguin Computing-built Corona high performance computing (HPC) cluster with an in-kind contribution of cutting-edge AMD Instinct™ accelerators, expected to nearly double the peak performance of the machine.

Lab researchers aid COVID-19 response in antibody, anti-viral research

Lawrence Livermore National Laboratory scientists are contributing to the global fight against COVID-19 by combining artificial intelligence/machine learning, bioinformatics and supercomputing to help discover candidates for new antibodies and pharmaceutical drugs to combat the disease.

Early research on existing drug compounds via supercomputing could combat coronavirus

Researchers at the Department of Energy’s Oak Ridge National Laboratory have used Summit, the world’s most powerful and smartest supercomputer, to identify 77 small-molecule drug compounds that might warrant further study in the fight against the SARS-CoV-2 coronavirus, which is responsible for the COVID-19 disease outbreak.

ORNL researchers develop ‘multitasking’ AI tool to extract cancer data in record time

To better leverage cancer data for research, scientists at ORNL are developing an artificial intelligence (AI)-based natural language processing tool to improve information extraction from textual pathology reports. In a first for cancer pathology reports, the team developed a multitask convolutional neural network (CNN)—a deep learning model that learns to perform tasks, such as identifying key words in a body of text, by processing language as a two-dimensional numerical dataset.

LLNL leads multi-institutional team in modeling protein interactions tied to cancer

Computational scientists, biophysicists and statisticians from Lawrence Livermore National Laboratory (LLNL) and Los Alamos National Laboratory (LANL) are leading a massive multi-institutional collaboration that has developed a machine learning-based simulation for next-generation supercomputers capable of modeling protein interactions and mutations that play a role in many forms of cancers.

Gordon Bell Finalist Team Tackles Transistors with New Programming Paradigm

A team simulated a 10,000-atom 2D transistor slice on the Summit supercomputer and mapped where heat is produced in a single transistor. Using a new data-centric version of the OMEN nanodevice simulator, the team sustained the code at 85.45 petaflops and earned a Gordon Bell Prize finalist nomination.

ORNL develops, deploys AI capabilities across research portfolio

To accelerate promising artificial intelligence applications in diverse research fields, ORNL has established a labwide AI Initiative. This internal investment brings the lab’s AI expertise, computing resources and user facilities together to facilitate analyses of massive datasets.

Study Uses Supercomputers to Advance Dynamic Earthquake Rupture Models

SDSC’s Comet Supports UC Riverside Study of San Andreas Fault System Multi-fault earthquakes can span fault systems of tens to hundreds of kilometers, with ruptures propagating from one segment to another. During the last decade, seismologists have observed several cases…