Today at Berkeley Lab

New Machine Learning for Science Website

Berkeley Lab recently launched a new site that showcases its wide array of machine learning projects spanning its divisions, disciplines, and areas of expertise. The Lab is developing advanced machine learning methods to analyze complex data sets that arise in DOE science and applied energy applications, such as biology and the environment, materials data from observation and simulation, high-end communication networks, and energy systems.

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Winners Emerge From DOE CyberForce Competition

More than 70 university teams representing seven DOE national labs competed this past weekend to defend their “network” from hackers played by security professionals and government representatives. The University of Central Florida won the national competition, while UC Davis bested three other teams representing Berkeley Lab. More>

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College Teams to Converge at Berkeley Lab for DOE CyberForce Competition

Four college teams – UC Berkeley, UC Davis, Cal State University San Bernardino, and Embry-Riddle Aeronautical University – will square off at Berkeley Lab this Saturday (Dec. 1) as part of DOE’s fourth collegiate CyberForce Competition. The event aims to address the cybersecurity capability gap and increase awareness around energy critical infrastructure. More>

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Four Berkeley Lab Scientists Named AAAS Fellows

Four Berkeley Lab scientists – Allen Goldstein (Energy Technologies Area), Sung-Hou Kim (Biosciences Area), Susannah Tringe (Biosciences Area), and Kathy Yelick (Computing Sciences) – have been named Fellows of the American Association for the Advancement of Science (AAAS), the world’s largest general scientific society. They are among 416 scientists awarded the distinction of AAAS Fellow this year. More>

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Berkeley Lab, Oak Ridge National Lab Share 2018 ACM Gordon Bell Prize

A team of computational scientists and engineers from Berkeley Lab, Oak Ridge National Laboratory, and NVIDIA has been awarded the ACM Gordon Bell Prize for applying an exascale-class deep learning application to extreme climate data, and for breaking the exaop (1 billion billion calculations) computing barrier for the first time with a deep learning application. More>

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DOE Undersecretary Dabbar Pens Op-Ed on Supercomputing

“When people hear “the Department of Energy,” they think, well, energy. But we do supercomputing, too. In fact, we are, and have been for almost every year since the 1950’s, the world’s leader in supercomputing,” writes DOE Undersecretary for Science Paul Dabbar in the Dallas Morning News. He also references the development of a new supercomputer at Berkeley Lab, to be named “Perlmutter.” More>

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Climate Simulations Project Wetter, Windier Hurricanes

New supercomputer simulations by climate scientists at Lawrence Berkeley National Laboratory have shown that climate change intensified the amount of rainfall in recent hurricanes such as Katrina, Irma, and Maria by 5 to 10 percent. They further found that if those hurricanes were to occur in a future world that is warmer than present, those storms would have even more rainfall and stronger winds. More>

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CRD’s Peisert to Discuss Data Sharing at National Academies’ COSEMPUP Meeting

Sean Peisert, a cybersecurity expert in the Lab’s Computational Research Division, will be part of two panels of distinguished speakers on the topic of data sharing at a meeting of the Committee on Science, Engineering, Medicine, and Public Policy, a joint unit of the National Academies of Sciences, Engineering, and Medicine, on Nov. 8 in Washington, D.C. More>

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Berkeley Lab Joins NSF-Funded ‘Cybersecurity Center of Excellence’ Collaboration

The National Science Foundation has awarded Trusted CI, an NSF Cybersecurity Center of Excellence (CCoE), a $2.5 million supplemental grant to expand its activities, such as transitioning cybersecurity research into practice to better secure the NSF community. Berkeley Lab is joining the collaboration, and Sean Peisert, the Lab’s chief cybersecurity researcher, is overseeing the Lab’s efforts in support of the CCoE. More>

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Team Breaks Exaop Barrier With Deep Learning Application

A team of computational scientists from Berkeley Lab and Oak Ridge National Laboratory and engineers from NVIDIA have, for the first time, demonstrated an exascale-class deep learning application that has broken the exaop barrier — an achievement that earned them a spot on this year’s list of finalists for the Gordon Bell Prize. More>

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