Berkeley Lab recently hosted the fourth annual X-Stack PI event, where X-Stack researchers, facilities teams, application scientists, and developers from national labs, universities, and industry met to share the latest developments in X-Stack application codes. “X-Stack was launched in 2012 by the U.S. Department of Energy’s Advanced Scientific Computing Research program to support the development of exascale software tools, including programming languages and libraries, compilers and runtime systems, that will help programmers handle massive parallelism, data movement, heterogeneity and failures as the scientific community transitions to the next generation of extreme-scale supercomputers.”
In this video from the 2016 Stanford HPC Conference, Gilad Shainer from the HPC Advisory Council moderates a panel discussion on Exascale Computing. “Exascale computing will uniquely provide knowledge leading to transformative advances for our economy, security and society in general. A failure to proceed with appropriate speed risks losing competitiveness in information technology, in our industrial base writ large, and in leading-edge science.”
In this video from the 2016 Stanford HPC Conference, Michael Jennings from LBNL presents: Node Health Check (NHC) Project Update. “In this follow-up to his 2014 presentation at the Stanford HPCAC Conference, Michael will provide an update on the latest happenings with the LBNL NHC project, new features in the latest release, and a brief overview of the roadmap for future development.”
Dr. Lewey Anton reports on who’s moving on up in High Peformance Computing. Familiar names in this edition include: Sharan Kalwani, John Lee, Jay Muelhoefer, Brian Sparks, and Ed Turkel. And be sure to let us know of HPC folks in new positions!
“This presentation will describe how OpenMP is used at NERSC. NERSC is the primary supercomputing facility for Office of Science in the US Depart of Energy (DOE). Our next production system will be an Intel Xeon Phi Knights Landing (KNL) system, with 60+ cores per node and 4 hardware threads per core. The recommended programming model is hybrid MPI/OpenMP, which also promotes portability across different system architectures.”
Today LBNL announced that a team of scientists from Berkeley Lab’s Computational Research Division has been awarded a grant by Intel to support their goal of enabling data analytics software stacks—notably Spark—to scale out on next-generation high performance computing systems.
Today ACM and IEEE announced that Kathy Yelick from LBNL will be the recipient of the 2015 ACM/IEEE Computer Society Ken Kennedy Award for innovative research contributions to parallel computing languages that have been used in both the research community and in production environments. She was also cited for her strategic leadership of the national research laboratories and for developing novel educational and mentoring tools. The award will be presented at SC15, which takes place Nov. 15-20, in Austin, Texas.
ESnet has released open source code for building online Interactive Network Portals. “Now that the libraries are made available, the team hopes that other organizations will take the code, use it, add to it and work with ESnet to make the improvements available to the community.”
A new breakthrough battery — one that has significantly higher energy, lasts longer, and is cheaper and safer — will likely be impossible without a new material discovery. And a new material discovery could take years, if not decades, since trial and error has been the best available approach. But Lawrence Berkeley National Laboratory (Berkeley Lab) scientist Kristin Persson says she can take some of the guesswork out of the discovery process with her Electrolyte Genome.
“I will describe a decade-long, multi-disciplinary, multi-institutional effort spanning neuroscience, supercomputing and nanotechnology to build and demonstrate a brain-inspired computer and describe the architecture, programming model and applications. I also will describe future efforts in collaboration with DOE to build, literally, a “brain-in-a-box”. The work was built on simulations conducted on Lawrence Livermore National Laboratory’s Dawn and Sequoia HPC systems in collaboration with Lawrence Berkeley National Laboratory.”