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Using models, 3D printing to study common heart defect
Aug. 10, 2020 -
One of the most common congenital heart defects, coarctation of the aorta (CoA) is a narrowing of the main artery transporting blood from the heart to the rest of the body. It affects more than 1,600 newborns each year in the United States, and can lead to health issues such as hypertension, premature coronary artery disease, aneurysms, stroke and cardiac failure. To better understand risk...
Advancing healthcare with data science (VIDEO)
Aug. 3, 2020 -
This video provides an overview of projects in which data scientists work with domain scientists to address major challenges in healthcare. To help fight the COVID-19 pandemic, researchers are developing computer models to search for potential antibody and antiviral drug treatments, sharing a data portal with scientists and the general public, and analyzing drug compounds via a novel text...
Software integration of AI accelerators in HPC (VIDEO)
July 31, 2020 -
In this episode of Next Platform TV, LLNL's Brian Van Essen talks about AI accelerator integration in HPC systems and software stacks. His interview begins at timestamp 27:57. Watch on YouTube.
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.
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.
The incorporation of machine learning into scientific simulations at LLNL (VIDEO)
May 5, 2020 -
In this video from the Stanford HPC Conference, Katie Lewis presents "The Incorporation of Machine Learning into Scientific Simulations at Lawrence Livermore National Laboratory." Read more and watch the video at insideHPC.
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...
Upgrades for LLNL supercomputer from AMD, Penguin Computing aid COVID-19 research
April 21, 2020 -
Under a new agreement, AMD will supply upgraded graphics accelerators for LLNL’s Corona supercomputing cluster, expected to nearly double the system’s peak compute power. The system will be used by scientists through the public/private COVID-19 HPC Consortium, and by LLNL researchers, who are working on discovering potential antibodies and anti-viral compounds for SARS-CoV-2, the virus that...
New partnership to unleash U.S. supercomputing resources in the fight against COVID-19
March 26, 2020 -
The White House announced the launch of the COVID-19 High Performance Computing Consortium to provide COVID-19 researchers worldwide with access to the world’s most powerful high performance computing resources that can significantly advance the pace of scientific discovery in the fight to stop the virus. Read more at LLNL News.
‘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...
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.
LLNL team achieves largest graph analytics to date
Oct. 28, 2019 -
Besides broad usage in the tech industry, graph analytics also have national security applications, where algorithms dig through massive datasets to find anomalies or patterns of nefarious activity. It’s in that vein that an LLNL team of computer scientists and applied mathematicians, including Roger Pearce, Geoffrey Sanders, postdoc Benjamin Priest and visiting scholar Trevor Steil, searched...
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...