Posts in tag

LLNL


Lawrence Livermore National Laboratory (LLNL) and Amazon Web Services (AWS) have signed a memorandum of understanding (MOU) to define the role of leadership-class high performance computing (HPC) in a future where cloud HPC is ubiquitous. Under the MOU, LLNL and AWS will explore software and hardware solutions spanning cloud and on-premises HPC environments, with the goal of establishing …

If a cancer patient tests positive for COVID-19, are they more likely to become hospitalized from the disease? That depends on certain risk factors, according to a new study by researchers at Lawrence Livermore National Laboratory (LLNL) and the University of California, San Francisco (UCSF), who looked to identify cancer-related risks for poor outcomes from COVID-19. Analyzing one of …

    An international team of scientists has found new biomarkers that can be used for diagnostic purposes and potentially as predictive tools of the risks associated with deep-space flight. In their study, the team, including three researchers from Lawrence Livermore National Laboratory (LLNL), examined approximately two-decade-old blood samples from space shuttle astronauts before and after flight. …

The Society for Industrial and Applied Mathematics (SIAM) announced Lawrence Livermore National Laboratory computational mathematician Rob Falgout as the recipient of the 2022 SIAM Activity Group on Supercomputing Career Prize. Established in 2009, the career prize recognizes “broad and distinguished contributions to the field of algorithms research and development for parallel scientific and engineering computing,” according to …

Lawrence Livermore National Laboratory (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 …

Registration is open through July 29 for the first-ever Machine Learning for Industry Forum (ML4I), a three-day virtual event starting Aug. 10. The forum aims to foster and illustrate the adoption of machine learning methods for practical industrial outcomes, with a strong emphasis on manufacturing. Over the course of the event, attendees will engage in …

Scientists developed a machine learning algorithm to predict 3D molecular crystal density from 2D chemical structures. A long-held goal by chemists across many industries, including energy, pharmaceuticals, energetics, food additives and organic semiconductors, is to imagine the chemical structure of a new molecule and be able to predict how it will function for a desired …

New research by Lawrence Livermore National Laboratory (LLNL) climate scientists and collaborators shows that satellite measurements of the temperature of the troposphere (the lowest region of the atmosphere) may have underestimated global warming over the last 40 years. The research appears in the Journal of Climate The team studied four different properties of tropical climate …

By applying modern machine learning and data science methods to “extreme” plasma physics, researchers can gain insight into our universe and find clues about creating a limitless amount of energy. In a recent perspective published in Nature, Lawrence Livermore National Laboratory (LLNL) scientists and international collaborators outline key challenges and future directions in using machine …

  Lawrence Livermore National Laboratory (LLNL) is looking for participants and attendees from industry, research institutions and academia for the first-ever Machine Learning for Industry Forum (ML4I), a three-day virtual event starting Aug. 10. Pre-registrations are open for the forum, which aims to foster and illustrate the adoption of machine learning methods for practical industrial …