The Lab was already using Elastic components to gather data from its HPC clusters, then investigated whether Elasticsearch and Kibana could be applied to all scanning and logging activities across the board.
As CTO of Livermore Computing, de Supinski is responsible for formulating, overseeing, and implementing LLNL’s large-scale computing strategy, requiring managing multiple collaborations with the HPC industry and academia.
LLNL participates in the ISC High Performance Conference (ISC23) on May 21–25.
Supercomputers broke the exascale barrier, marking a new era in processing power, but the energy consumption of such machines cannot run rampant.
UCLA's Institute for Pure & Applied Mathematics hosted LLNL's Erik Draeger for a talk about the challenges and possibilities of exascale computing.
Combining specialized software tools with heterogeneous HPC hardware requires an intelligent workflow performance optimization strategy.
LLNL is participating in the 34th annual Supercomputing Conference (SC22), which will be held both virtually and in Dallas on November 13–18, 2022.
The second article in a series about the Lab's stockpile stewardship mission highlights computational models, parallel architectures, and data science techniques.
The first article in a series about the Lab's stockpile stewardship mission highlights the roles of computer simulations and exascale computing.
The new oneAPI Center of Excellence will involve the Center for Applied Scientific Computing and accelerate ZFP compression software to advance exascale computing.
LLNL participates in the CMD-IT/ACM Richard Tapia Celebration of Diversity in Computing Conference (Tapia2022) on September 7–10.
The Advanced Technology Development and Mitigation program within the Exascale Computing Project shows that the best way to support the mission is through open collaboration and a sustainable software infrastructure.
LLNL has signed a memorandum of understanding with HPC facilities in Germany, the United Kingdom, and the U.S., jointly forming the International Association of Supercomputing Centers.
The Lab's upcoming exascale-capable supercomputer will see an implementation of a converged accelerated computing unit, or APU, hybrid CPU-GPU compute engine.
In a presentation delivered to the 79th HPC User Forum at Oak Ridge National Laboratory, LLNL's Terri Quinn revealed that AMD’s forthcoming MI300 APU would be the computational bedrock of El Capitan, which is slated for installation at LLNL in late 2023.
The utility-grade infrastructure project massively upgraded the power and water-cooling capacity of the adjacent Livermore Computing Center, preparing it to house next generation exascale-class supercomputers for NNSA.
As the U.S. welcomed the world’s first “true” exascale supercomputer, three predecessor machines for LLNL's future exascale system El Capitan managed to rank highly on the latest Top500 List of the world’s most powerful supercomputers.
The Exascale Computing Project (ECP) 2022 Community Birds-of-a-Feather Days will take place May 10–12 via Zoom. The event provides an opportunity for the HPC community to engage with ECP teams to discuss our latest development efforts.
El Capitan will have a peak performance of more than 2 exaflops—roughly 16 times faster on average than the Sierra system—and is projected to be several times more energy efficient than Sierra.
LC sited two different AI accelerators in 2020: the Cerebras wafer-scale AI engine attached to Lassen; and an AI accelerator from SambaNova Systems into the Corona cluster.
The DOE's Exascale Computing Project compiled a video playlist for Exascale Day on October 18 (1018).
Though the arrival of the exascale supercomputer El Capitan at LLNL is still almost two years away, teams of code developers are busy working on predecessor systems to ensure critical applications are ready for Day One.
To prepare for the next generation of power-hungry supercomputers, LLNL crews have been working throughout the pandemic on a $100 million Exascale Computing Facility Modernization project.
A newly funded project involving LLNL computer scientist Ignacio Laguna will examine numerical aspects of porting scientific applications to different HPC platforms.
A Livermore-developed programming approach helps software to run on different platforms without major disruption to the source code.