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Introduction to deep learning for image classification workshop (VIDEO)
July 6, 2022 -
In addition to its annual conference held every March, the global Women in Data Science (WiDS) organization hosts workshops and other activities year-round to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field. On June 29, LLNL’s Cindy Gonzales led a WiDS Workshop titled “Introduction to Deep Learning for Image Classification.” The abstract...
Assured and robust…or bust
June 30, 2022 -
The consequences of a machine learning (ML) error that presents irrelevant advertisements to a group of social media users may seem relatively minor. However, this opacity, combined with the fact that ML systems are nascent and imperfect, makes trusting their accuracy difficult in mission-critical situations, such as recognizing life-or-death risks to military personnel or advancing materials...
UC Merced students work with LLNL mentors on potential new drugs to combat COVID-19
June 30, 2022 -
Students from the University of California, Merced worked with mentors at LLNL to identify drug compounds that could be used to treat COVID-19 during a two-week Data Science Challenge (DSC) that concluded on June 6. For the first time in the DSC series since the COVID-19 pandemic began in 2020, Lab mentors visited the college campus to provide in-person guidance for five teams of UC Merced...
NNSA Administrator Hruby dedicates LLNL’s computing facility upgrade
June 20, 2022 -
On June 15, Department of Energy Under Secretary for Nuclear Security and Administrator for the National Nuclear Security Administration (NNSA) Jill Hruby dedicated two critical infrastructure projects at LLNL, part of a three-day visit to the Lab. Hruby attended ribbon-cutting ceremonies for the Exascale Computing Facility Modernization (ECFM) project and LLNL’s new Emergency Operations...
LLNL’s Brase discusses advances by ATOM in accelerating drug discovery pipeline
June 7, 2022 -
The private-public Accelerating Therapeutic Opportunities in Medicine (ATOM) consortium is showing “significant” progress in demonstrating that HPC and M) tools can speed up the drug discovery process, said Jim Brase, ATOM co-lead and LLNL’s deputy associate director for data science. The consortium currently boasts more than a dozen member organizations, including national laboratories...
El Capitan testbed systems rank among top 200 of world’s most powerful computers
June 1, 2022 -
As the U.S. welcomed the world’s first “true” exascale supercomputer, three predecessor machines for LLNL's future exascale system El Capitan managed to rank highly on the latest Top500 List of the world’s most powerful supercomputers. Despite being “testbed” machines for El Capitan, the National Nuclear Security Administration’s first exascale supercomputer, the three early access systems...
HPCIC webinar series to highlight LLNL/Hartree Center industry engagement and joint research
May 19, 2022 -
LLNL and the United Kingdom’s Hartree Centre are launching a new webinar series intended to spur collaboration with industry through discussions on computational science, HPC, and data science. The first Hartree–Livermore joint webinar on Computational Science (HLCS) takes place May 24, where speakers from the Hartree Centre will present industrial collaboration efforts and technical work...
Kevin McLoughlin applies computational biology to complex problems
May 17, 2022 -
Kevin McLoughlin has always been fascinated by the intersection of computing and biology. His LLNL career encompasses award-winning microbial detection technology, a COVID-19 antiviral drug design pipeline, and work with the ATOM consortium. The appeal for him in these projects lies at the intersection of computing and biology. “I love finding ways to visualize data that reveal relationships...
NNSA and Cornelis Networks to collaborate on next-generation high-performance networking
May 4, 2022 -
The Next-Generation High Performance Computing Network (NG-HPCN) project for the NNSA’s Advanced Simulation and Computing (ASC) program will enable NNSA to co-design and partner with Cornelis on development and productization of next-generation interconnect technologies for HPC. The project is led by LLNL for the NNSA Tri-Labs: LLNL, Los Alamos and Sandia national laboratories. The resulting...
Accelerating the path to precision medicine
March 22, 2022 -
LLNL joined the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) consortium in 2018. The national, multiyear, multidisciplinary effort, led by the University of California at San Francisco in collaboration with Lawrence Berkeley and Argonne national laboratories and other leading research organizations and universities, combines neuroimaging, blood-based...
Machine learning model finds COVID-19 risks for cancer patients
March 10, 2022 -
A new study by researchers at LLNL and the University of California, San Francisco, looks to identify cancer-related risks for poor outcomes from COVID-19. Analyzing one of the largest databases of patients with cancer and COVID-19, the team found previously unreported links between a rare type of cancer—as well as two cancer treatment-related drugs—and an increased risk of hospitalization...
Winter hackathon meets WiDS datathon
March 9, 2022 -
Sponsored by the DSI, LLNL’s winter hackathon took place on February 16–17. Hackathons are 24-hour events that encourage collaborative programming and creative problem solving. In addition to traditional hacking, the hackathon included a special datathon competition in anticipation of the Women in Data Science (WiDS) conference on March 7. Hackathon and datathon participants presented their...
LLNL team models COVID-19 disease progression and identifies risk factors
Feb. 15, 2022 -
An LLNL team has developed a comprehensive dynamic model of COVID-19 disease progression in hospitalized patients, finding that risk factors for complications from the disease are dependent on the patient’s disease state. Using a machine learning algorithm on a dataset of electronic health records from more than 1,300 hospitalized COVID-19 patients with ProMedica — the largest health care...
COVID-19 R&D: Computing responds to pandemic
Jan. 19, 2022 -
When the COVID-19 pandemic began, the Laboratory immediately started seeking solutions to the myriad challenges posed by the global crisis. The Computing Directorate jumped right in with research and development activities that combine molecular screening to inform antiviral drug experimentation; a generative molecular design software platform to optimize properties of antiviral drugs; an...
LLNL establishes AI Innovation Incubator to advance artificial intelligence for applied science
Dec. 20, 2021 -
LLNL has established the AI Innovation Incubator (AI3), a collaborative hub aimed at uniting experts in artificial intelligence (AI) from LLNL, industry and academia to advance AI for large-scale scientific and commercial applications. LLNL has entered into a new memoranda of understanding with Google, IBM and NVIDIA, with plans to use the incubator to facilitate discussions and form future...
Career panel spotlights diversity, equity, and inclusion
Nov. 19, 2021 -
The DSI’s career panel series continued on November 3 with a session highlighting diversity, equity, and inclusion (DEI) as well as the Lab’s DEI-focused employee resource groups (ERGs). ERGs are sponsored by LLNL’s Office of Strategic Diversity and Inclusion Programs.
Moderator Anh Quach, member of the Asian Pacific American Council (APAC), was joined by four panelists: Raul Viera Mercado...
U.S. Department of Energy to showcase national lab expertise at SC21
Nov. 11, 2021 -
The scientific computing and networking leadership of the U.S. Department of Energy’s (DOE’s) national laboratories will be on display at SC21, the International Conference for High-Performance Computing, Networking, Storage and Analysis. The conference takes place Nov. 14-19 in St. Louis via a combination of on-site and online resources. The theme of this year’s conference is “Science and...
Building confidence in materials modeling using statistics
Oct. 31, 2021 -
LLNL statisticians, computational modelers, and materials scientists have been developing a statistical framework for researchers to better assess the relationship between model uncertainties and experimental data. The Livermore-developed statistical framework is intended to assess sources of uncertainty in strength model input, recommend new experiments to reduce those sources of uncertainty...
LLNL joins Human Vaccines Project to accelerate vaccine development and understanding of immune response
Oct. 21, 2021 -
LLNL has joined the international Human Vaccines Project (HVP), bringing Lab expertise and computing resources to the consortium to aid development of a universal coronavirus vaccine and improve understanding of immune response. The HVP is a nonprofit, public-private partnership with a mission to decode the human immune system and accelerate the development of vaccines and immunotherapies...
Summer scholar develops data-driven approaches to key NIF diagnostics
Oct. 20, 2021 -
Su-Ann Chong's summer project, “A Data-Driven Approach Towards NIF Neutron Time-of-Flight Diagnostics Using Machine Learning and Bayesian Inference,” is aimed at presenting a different take on nToF diagnostics. Neutron time-of-flight diagnostics are an essential tool to diagnose the implosion dynamics of inertial confinement fusion experiments at NIF, the world’s largest and most energetic...