Data Science in the News

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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...

LLNL, ANL and GSK provide early glimpse into Cerebras AI system performance

Oct. 13, 2020 - 
AI chip and systems startup Cerebras was one of many AI companies showcased at the AI Hardware Summit which concluded last week. Cerebras invited collaborators from LLNL, Argonne National Laboratory, and GlaxoSmithKline to talk about their early work on Cerebras machines and future plans. Livermore Computing's CTO Bronis de Supinski said, “We have this vision for performing cognitive...

Machine learning speeds up and enhances physics calculations

Oct. 1, 2020 - 
Interpreting data from NIF’s cutting-edge high energy density science experiments relies on physics calculations that are so complex they can challenge LLNL supercomputers, which stand among the best in the world. A collaboration between LLNL and French researchers found a novel way to incorporate machine learning and neural networks to significantly speed up inertial confinement fusion...

Machine learning model may perfect 3D nanoprinting

July 29, 2020 - 
Two-photon lithography (TPL)—a widely used 3D nanoprinting technique that uses laser light to create 3D objects—has shown promise in research applications but has yet to achieve widespread industry acceptance due to limitations on large-scale part production and time-intensive setup. LLNL scientists and collaborators turned to machine learning to address two key barriers to industrialization...

Lockdown doesn’t hinder annual Data Science Challenge

June 26, 2020 - 
Due to the COVID-19 pandemic and shelter-in-place restrictions, this year’s Data Science Challenge with the University of California, Merced was an all-virtual offering. The two-week challenge involved 21 UC Merced students who worked from their homes through video conferencing and chat programs to develop machine learning models capable of differentiating potentially explosive materials from...

DL-based surrogate models outperform simulators and could hasten scientific discoveries

June 17, 2020 - 
Surrogate models supported by neural networks can perform as well, and in some ways better, than computationally expensive simulators and could lead to new insights in complicated physics problems such as inertial confinement fusion (ICF), LLNL scientists reported. Read more at LLNL News.

Modeling neuronal cultures on 'brain-on-a-chip' devices

June 12, 2020 - 
For the past several years, LLNL scientists and engineers have made significant progress in development of a three-dimensional “brain-on-a-chip” device capable of recording neural activity of human brain cell cultures grown outside the body. The team has developed a statistical model for analyzing the structures of neuronal networks that form among brain cells seeded on in vitro brain-on-a...

AI identifies change in microstructure in aging materials

May 26, 2020 - 
LLNL scientists have taken a step forward in the design of future materials with improved performance by analyzing its microstructure using AI. The work recently appeared online in the journal Computational Materials Science. Read more at LLNL News.

AI hardware for future HPC systems (VIDEO)

May 20, 2020 - 
This interview with Brian Spears, who leads cognitive simulations at LLNL, covers the current state of evaluation of AI chips and how those will mesh with existing and future HPC systems. Watch on YouTube.

Building knowledge and insights using machine learning of scientific articles

May 5, 2020 - 
Nanomaterials are widely used at LLNL and in industry for many applications from catalysis to optics to additive manufacturing. The combination of nanomaterials’ shape, size, and composition can impart unique optical, electrical, mechanical, or catalytic properties needed for a specific application. However, synthesizing a specific nanomaterial and scaling up its production is often...

Lab promotes diversity, tech at Women in Data Science regional event

April 3, 2020 - 
For the third consecutive year, Lawrence Livermore National Laboratory (LLNL) hosted a Women in Data Science (WiDS) regional event on March 2. Held at the HPC Innovation Center, the event drew dozens of attendees from LLNL, Sandia National Laboratories, local universities, and Bay Area commercial companies. Livermore was one of over 200 regional events in 60 countries coordinated with the...

Local Women in Data Science conference showcases Lab research

April 3, 2020 - 
For the third consecutive year, LLNL hosted a Women in Data Science (WiDS) regional event on March 2. The event drew dozens of attendees from LLNL, Sandia National Laboratories, local universities, and Bay Area commercial companies. Livermore was one of over 200 regional events in 60 countries coordinated with the main WiDS conference at Stanford University. According to the WiDS website...

‘Yes, you can’: UC Merced students learning, growing at Livermore Lab

Feb. 26, 2020 - 
Just 90 miles UC Merced lies one of the epicenters of the future of technology, innovation and national security. The university and lab have teamed up to lay the groundwork for a direct pipeline between the two, opening a door to research collaborations as well as job and internship opportunities for students and alumni. Read more at UC Merced.

Machine learning accelerates high-performance materials development

Feb. 13, 2020 - 
Lawrence Livermore National Laboratory (LLNL) and its partners rely on timely development and deployment of diverse materials to support a variety of national security missions. However, materials development and deployment can take many years from initial discovery of a new material to deployment at scale. Now, an interdisciplinary team of LLNL researchers from the Physical and Life Sciences...

Deep learning may provide solution for efficient charging, driving of autonomous electric vehicles

Feb. 4, 2020 - 
LLNL computer scientists and software engineers have developed a deep learning-based strategy to maximize electric vehicle (EV) ride-sharing services while reducing carbon emissions and the impact to the electrical grid, emphasizing autonomous EVs capable of offering 24-hour service. Read more at LLNL News.

Department of Energy researchers share data management strategies at first-ever “Data Day”

Nov. 11, 2019 - 
It’s become something of a mantra of the digital age: Data is the new currency. Especially in science, where it’s hard to find a single project that doesn’t involve generating or consuming massive amounts of data. In light of the growing awareness of the critical importance of data management across the Department of Energy complex, more than 100 researchers from DOE national laboratories...

Big data illuminates the physical sciences

Nov. 6, 2019 - 
Livermore teams are applying innovative data analysis and interpretation techniques to advance fundamental science research. This article describes projects in astrophysics and materials science. Read more at Science & Technology Review.

Successful simulation and visualization coupling proves the power of Sierra

Oct. 22, 2019 - 
As the first National Nuclear Security Administration (NNSA) production supercomputer backed by GPU- (graphics processing unit) accelerated architecture, Sierra’s acquisition required a fundamental shift in how scientists at Lawrence Livermore National Laboratory (LLNL) program their codes to take advantage of the GPUs. The majority of Sierra’s computational power—95 percent of its 125...

Collaboration drives data science workshop

Sept. 12, 2019 - 
Lawrence Livermore National Laboratory’s (LLNL’s) Data Science Institute (DSI) hosted its second annual workshop on July 23–24, 2019. Co-sponsored by the University of California (UC) system, the event drew more than 200 participants to Garré Winery in Livermore. A common theme ran throughout both days: Collaboration is always welcome. Indeed, feedback from last year’s workshop inspired a...

Livermore Lab Foundation awards scholarship to Cal State East Bay computer science student

Aug. 2, 2019 - 
Alan Noun, a computer science student at Cal State University East Bay and the recipient of the Livermore Lab Foundation's first full-year scholarship, has started a summer internship at LLNL. In partnership with Cal State University East Bay (CSUEB), the Livermore Lab Foundation (LLF) awarded Noun a one-year stipend to allow him to devote more time to academics by reducing work he needs to...