Researchers at SDSC have developed a new seismic software package with Intel Corporation that has enabled the fastest seismic simulation to-date. SDSC’s ground-breaking performance of 10.4 Petaflops on earthquake simulations used 612,000 Intel Xeon Phi processor cores of the new Cori Phase II supercomputer at NERSC.
Following a call for proposals issued last October, NERSC has selected six science application teams to participate in the NERSC Exascale Science Applications Program for Data (NESAP for Data) program. “We’re very excited to welcome these new data-intensive science application teams to NESAP,” said Rollin Thomas, a big data architect in NERSC’s Data Analytics and Services group who is coordinating NESAP for Data. “NESAP’s tools and expertise should help accelerate the transition of these data science codes to KNL. But I’m also looking forward to uncovering and understanding the new performance and scalability challenges that are sure to arise along the way.”
“This is an exciting time because the whole HPC landscape is changing with manycore, which is a big change for our users,” said Gerber, who joined NERSC’s User Services Group in 1996 as a postdoc, having earned his PhD in physics from the University of Illinois. “Users are facing a big challenge; they have to be able to exploit the architectural features on Cori (NERSC’s newest supercomputing system), and the HPC Department plays a critical role in helping them do this.”
A new study led by a research scientist at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) highlights a literally shady practice in plant science that has in some cases underestimated plants’ rate of growth and photosynthesis, among other traits. “More standardized fieldwork, in parallel with new computational tools and theoretical work, will contribute to better global plant models,” Keenan said.
Using a unique computational approach to rapidly sample proteins in their natural state of gyrating, bobbing, and weaving, a research team from UC San Diego and Monash University in Australia has identified promising drug leads that may selectively combat heart disease, from arrhythmias to cardiac failure.
In this video from the Intel HPC Developer Conference, Prabhat from NERSC describes how high performance computing techniques are being used to scale Machine Learning to over 100,000 compute cores. “Using TB-sized datasets from three science applications: astrophysics, plasma physics, and particle physics, we show that our implementation can construct kd-tree of 189 billion particles in 48 seconds on utilizing ∼50,000 cores.”
Researchers and staff from the U.S. Department of Energy’s national laboratories will showcase some of DOE’s best computing and networking innovations and techniques at SC16 in Salt Lake City. “Computational scientists working for various DOE laboratories have been in involved in the conference since its 1988 beginnings, and this year’s event is no different. Experts from 14 national laboratories will be sharing a booth featuring speakers, presentations, demonstrations, discussions and simulations.”
Researchers at the Department of Energy’s SLAC National Accelerator Laboratory are playing key roles in two recently funded computing projects with the goal of developing cutting-edge scientific applications for future exascale supercomputers that can perform at least a billion billion computing operations per second – 50 to 100 times more than the most powerful supercomputers in the world today.
NERSC is working with Cray to explore new ways to more efficiently move data in and out of Cori, a powerful supercomputer being constructed in California. “We need to take advantage of a network guru’s design for moving data for a specific experiment but have SDN do all of the bookkeeping for which compute nodes need to be connected to what networks,” said Brent Draney, group lead for the Networking, Servers and Security Group at NERSC. “I would rather see our network engineers analyze the data flow and how to meet the need instead of having to manually reconfigure the network for the demands of each job.”
“Being ready with full support for Intel Xeon Phi from day one has been a key strategy for Allinea and underpins our approach for supporting customers, such as Los Alamos National Laboratory on the Trinity system, Argonne National Laboratory on Theta and NERSC on Cori, where work is now underway to port code and get applications ready for more complex science on a larger scale.”