Data Science in the News

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High-performance computing, AI and cognitive simulation helped LLNL conquer fusion ignition

June 21, 2023 - 
For hundreds of LLNL scientists on the design, experimental, and modeling and simulation teams behind inertial confinement fusion (ICF) experiments at the National Ignition Facility, the results of the now-famous Dec. 5, 2022, ignition shot didn’t come as a complete surprise. The “crystal ball” that gave them increased pre-shot confidence in a breakthrough involved a combination of detailed...

Visionary report unveils ambitious roadmap to harness the power of AI in scientific discovery

June 12, 2023 - 
A new report, the product of a series of workshops held in 2022 under the guidance of the U.S. Department of Energy’s Office of Science and the National Nuclear Security Administration, lays out a comprehensive vision for the Office of Science and NNSA to expand their work in scientific use of AI by building on existing strengths in world-leading high performance computing systems and data...

Data science meets fusion (VIDEO)

May 30, 2023 - 
LLNL’s historic fusion ignition achievement on December 5, 2022, was the first experiment to ever achieve net energy gain from nuclear fusion. However, the experiment’s result was not actually that surprising. A team leveraging data science techniques developed and used a landmark system for teaching artificial intelligence (AI) to incorporate and better account for different variables and...

LLNL and SambaNova Systems announce additional AI hardware to support Lab’s cognitive simulation efforts

May 23, 2023 - 
LLNL and SambaNova Systems have announced the addition of a spatial data flow accelerator into the Livermore Computing Center, part of an effort to upgrade the Lab’s CogSim program. LLNL will integrate the new hardware to further investigate CogSim approaches combining AI with high-performance computing—and how deep neural network hardware architectures can accelerate traditional physics...

Cognitive simulation supercharges scientific research

Jan. 10, 2023 - 
Computer modeling has been essential to scientific research for more than half a century—since the advent of computers sufficiently powerful to handle modeling’s computational load. Models simulate natural phenomena to aid scientists in understanding their underlying principles. Yet, while the most complex models running on supercomputers may contain millions of lines of code and generate...

Supercomputing’s critical role in the fusion ignition breakthrough

Dec. 21, 2022 - 
On December 5th, the research team at LLNL's National Ignition Facility (NIF) achieved a historic win in energy science: for the first time ever, more energy was produced by an artificial fusion reaction than was consumed—3.15 megajoules produced versus 2.05 megajoules in laser energy to cause the reaction. High-performance computing was key to this breakthrough (called ignition), and HPCwire...

LLNL staff returns to Texas-sized Supercomputing Conference

Nov. 23, 2022 - 
The 2022 International Conference for High Performance Computing, Networking, Storage, and Analysis (SC22) returned to Dallas as a large contingent of LLNL staff participated in sessions, panels, paper presentations, and workshops centered around HPC. The world’s largest conference of its kind celebrated its highest in-person attendance since the start of the COVID-19 pandemic, with about 11...

LLNL researchers win HPCwire award for applying cognitive simulation to ICF

Nov. 17, 2022 - 
The high performance computing publication HPCwire announced LLNL as the winner of its Editor’s Choice award for Best Use of HPC in Energy for applying cognitive simulation (CogSim) methods to inertial confinement fusion (ICF) research. The award was presented at the largest supercomputing conference in the world: the 2022 International Conference for High Performance Computing, Networking...

Scientific discovery for stockpile stewardship

Sept. 27, 2022 - 
Among the significant scientific discoveries that have helped ensure the reliability of the nation’s nuclear stockpile is the advancement of cognitive simulation. In cognitive simulation, researchers are developing AI/ML algorithms and software to retrain part of this model on the experimental data itself. The result is a model that “knows the best of both worlds,” says Brian Spears, a...

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...

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...

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...

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...

60 years of cancer research

Sept. 10, 2021 - 
From studying radioactive isotope effects to better understanding cancer metastasis, the Laboratory’s relationship with cancer research endures some 60 years after it began, with historical precedent underpinning exciting new research areas. In one Cancer Moonshot project, research includes a close synergy between experiments and computation, allowing scientists to get a better picture of the...

COVID-19 detection and analysis with Nisha Mulakken (VIDEO)

June 7, 2021 - 
LLNL biostatistician Nisha Mulakken has enhanced the Lawrence Livermore Microbial Detection Array (LLMDA) system with detection capability for all variants of SARS-CoV-2. The technology detects a broad range of organisms—viruses, bacteria, archaea, protozoa, and fungi—and has demonstrated novel species identification for human health, animal health, biodefense, and environmental sampling...

CASC research in machine learning robustness debuts at AAAI conference

Feb. 10, 2021 - 
LLNL’s Center for Applied Scientific Computing (CASC) has steadily grown its reputation in the artificial intelligence (AI)/machine learning (ML) community—a trend continued by three papers accepted at the 35th AAAI Conference on Artificial Intelligence, held virtually on February 2–9, 2021. Computer scientists Jayaraman Thiagarajan, Rushil Anirudh, Bhavya Kailkhura, and Peer-Timo Bremer led...

What put LLNL at the center of U.S. supercomputing in 2020?

Nov. 12, 2020 - 
The HPC world is waiting for the next series of transitions to far larger machines with exascale capabilities. By this time next year, the bi-annual ranking of the Top500 most powerful systems will be refreshed at the top as Frontier, El Capitan, Aurora, and other DOE systems come online. While LLNL was already planning around AI acceleration for its cognitive simulation aims and had a number...

From intern to mentor, Nisha Mulakken builds a career in bioinformatics

Nov. 3, 2020 - 
The COVID-19 pandemic has sparked a wave of new research and development at the Lab, and Nisha Mulakken is very busy. The biostatistician has enhanced the Lawrence Livermore Microbial Detection Array (LLMDA) system with detection capability for all variants of SARS-CoV-2. The technology detects a broad range of organisms—viruses, bacteria, archaea, protozoa, and fungi—and has demonstrated...

AI gets a boost via LLNL, SambaNova collaboration

Oct. 20, 2020 - 
LLNL has installed a state-of-the-art artificial intelligence (AI) accelerator from SambaNova Systems, the National Nuclear Security Administration (NNSA) announced today, allowing researchers to more effectively combine AI and machine learning (ML) with complex scientific workloads. LLNL has begun integrating the new AI hardware, SambaNova Systems DataScale™, into the NNSA’s Corona...