Data Science in the News

El Capitan verified as world's fastest supercomputer

LLNL, in collaboration with the National Nuclear Security Administration (NNSA), Hewlett Packard Enterprise and AMD, have officially unveiled El Capitan as the world's most powerful supercomputer and first exascale system dedicated to national security. Verified at 1.742 exaflops (1.742 quintillion calculations per second) on the High Performance Linpack—the standard benchmark used by the...

ICECap looks to use exascale fusion simulations to pioneer digital design

A groundbreaking multidisciplinary team of LLNL researchers is combining the power of exascale computing with AI, advanced workflows and graphics processor (GPU)-acceleration to advance scientific innovation and revolutionize digital design. The project, called ICECap (Inertial Confinement on El Capitan), is a transformative approach to inertial confinement fusion (ICF) design optimization...

DOE honors seven early-career Lab scientists

Seven LLNL scientists are recipients of the DOE's Office of Science Early Career Research Program (ECRP) award. Among them is Shusen Liu, a computer scientist in the Machine Intelligence Group in the Center for Applied Scientific Computing. His work focuses on understanding and interpreting the inner mechanisms of neural networks and integrating human domain knowledge with machine...

LLNL, DOD, NNSA dedicate Rapid Response Laboratory and supercomputing system to accelerate biodefense

LLNL recently welcomed officials from the Department of Defense (DOD) and National Nuclear Security Administration (NNSA) to dedicate a new supercomputing system and Rapid Response Laboratory (RRL). DOD is working with NNSA to significantly increase the computing capability available to the national biodefense programs. The collaboration has enabled expanding systems of the same architecture...

ISCP projects make machine learning advantages tangible

Data science tools are not only rapidly taking hold across disciplines, they are constantly evolving. The applications, services, and techniques one cohort of scientists and engineers may have learned could be out of date by the next cohort, especially as machine learning (ML) and artificial intelligence (AI) tools become commonplace. To keep employees abreast of the latest tools, two data...

LLNL and BridgeBio announce trials for supercomputing-discovered cancer drug

In a substantial milestone for supercomputing-aided drug design, LLNL and BridgeBio Oncology Therapeutics (BridgeBio) today announced clinical trials have begun for a first-in-class medication that targets specific genetic mutations implicated in many types of cancer. The development of the new drug—BBO-8520—is the result of collaboration among LLNL, BridgeBio and the National Cancer...

The Laboratory’s habit of innovation

LLNL’s HPC and data science capabilities play a significant role in international science research and innovation, and Lab researchers have won 10 R&D 100 Awards in the Software–Services category in the past decade. The latest issue of Science & Technology Review features several award-winning projects, including ZFP and CANDLE: (1) ZFP introduces a new method of compressing large data sets...

Statistical framework synchronizes medical study data

The risks and benefits of heart surgery, chemotherapy, vaccination, and other medical treatments can change based on the time of day they are administered. These variations arise in part due to changes in gene expression levels throughout the 24-hour day-night cycle, with around 50% of genes displaying oscillatory behavior. To evaluate new therapies, investigators study how a gene’s...

GUIDE team develops approach to redesign antibodies against viral pandemics

In a groundbreaking development for addressing future viral pandemics, a multi-institutional team involving LLNL researchers has successfully combined an AI-backed platform with supercomputing to redesign and restore the effectiveness of antibodies whose ability to fight viruses has been compromised by viral evolution. The team’s research is published in the journal Nature and showcases a...

Welcome new DSI team members

When Data Science Institute (DSI) director Brian Giera and deputy director Cindy Gonzales began planning activities for fiscal year 2024 and beyond, they immediately realized that LLNL’s growth in data science and artificial intelligence (AI)/machine learning (ML) research requires corresponding growth in the DSI’s efforts. “Our field is booming,” Giera states. “The Lab has a stake in the...

WiDS Livermore conference attendees network, share research and absorb wisdom

Co-sponsored by the DSI, LLNL on March 13 hosted the 7th annual Women in Data Science (WiDS) conference for data scientists, industry professionals, recent graduates and others interested in the field. As an independent satellite of the global WiDS conference celebrating International Women’s Day, the Livermore hybrid event was held to highlight the work and careers of LLNL and regional data...

Machine learning tool fills in the blanks for satellite light curves

When viewed from Earth, objects in space are seen at a specific brightness, called apparent magnitude. Over time, ground-based telescopes can track a specific object’s change in brightness. This time-dependent magnitude variation is known as an object’s light curve, and can allow astronomers to infer the object’s size, shape, material, location, and more. Monitoring the light curve of...

Register for WiDS Livermore on March 13

The annual Women in Data Science (WiDS) conference returns on Wednesday, March 13. This is the seventh year for WiDS Livermore, which is independently organized by LLNL to be part of the mission to increase participation of women in data science and to feature outstanding women doing outstanding work. The all-day WiDS Livermore event is free and will be presented in a hybrid format. Everyone...

Conference paper illuminates neural image compression

An enduring question in machine learning (ML) concerns performance: How do we know if a model produces reliable results? The best models have explainable logic and can withstand data perturbations, but performance analysis tools and datasets that will help researchers meaningfully evaluate these models are scarce. A team from LLNL’s Center for Applied Scientific Computing (CASC) is teasing...

Data Days brings DOE labs together for discussions on data management and more

Data researchers, developers, data managers, and program managers from the DOE national laboratories visited LLNL on October 24–26 to discuss the latest in data management, sharing, and accessibility at the 2023 DOE Data Days (D3) workshop. Sponsored by the National Nuclear Security Administration’s (NNSA) Office of Defense Nuclear Nonproliferation and hosted annually by LLNL, the event...

Making machine learning safer for biomedicine

It’s hard to understate the impact machine learning will have on biomedicine. The ability to train computers to spot patterns by analyzing large, complex datasets is driving discoveries in heart disease, cancer, neurodegenerative diseases and more. For instance, Argonne National Laboratory (ANL) has used machine learning to aid cancer research and accelerate COVID-19 antiviral discovery. One...

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

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...

Consulting service infuses Lab projects with data science expertise

A key advantage of LLNL’s culture of multidisciplinary teamwork is that domain scientists don’t need to be experts in everything. Physicists, chemists, biologists, materials engineers, climate scientists, computer scientists, and other researchers regularly work alongside specialists in other fields to tackle challenging problems. The rise of Big Data across the Lab has led to a demand for...

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

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...

Celebrating the DSI’s first five years

View the LLNL Flickr album Data Science Institute Turns Five. Data science—a field combining technical disciplines such as computer science, statistics, mathematics, software development, domain science, and more—has become a crucial part of how LLNL carries out its mission. Since the DSI’s founding in 2018, the Lab has seen tremendous growth in its data science community and has invested...