Topic: HPC Systems and Software

Hosted at LLNL, the Center for Efficient Exascale Discretizations’ annual event featured breakout discussions, more than two dozen speakers, and an evening of bocce ball.

Tammy Dahlgren has worked on a diverse variety of projects at the Lab, including supervisory control systems for the National Ignition Facility, animal disease modeling, mass hierarchical storage systems, RADIUSS, and more.

With this year’s results, the Lab has now collected a total of 179 R&D 100 awards since 1978. The awards will be showcased at the 61st R&D 100 black-tie awards gala on Nov. 16 in San Diego.

A team from LLNL and seven other DOE labs is a finalist for the new ACM Gordon Bell Prize for Climate Modeling for running an unprecedented high-resolution global atmosphere model on the world’s first exascale supercomputer. 

LLNL's Ian Lee joins a Dots and Bridges panel to discuss HPC as a critical resource for data assimilation and numerical weather prediction research.

LLNL's zfp and Variorum software projects are winners. LLNL is a co-developing organization on the winning CANDLE project.

Collecting variants in low-level hardware features across multiple GPU and CPU architectures.

The Tri-Lab Operating System Stack (TOSS) ensures other national labs’ supercomputing needs are met.

Livermore Computing is making significant progress toward siting the NNSA’s first exascale supercomputer.

Innovative hardware provides near-node local storage alongside large-capacity storage.

Siting a supercomputer requires close coordination of hardware, software, applications, and Livermore Computing facilities.

Flux, next-generation resource and job management software, steps up to support emerging use cases.

Livermore builds an open-source community around its award-winning HPC package manager.

A Laboratory-developed software package management tool, enhanced by contributions from more than 1,000 users, supports the high performance computing community.

Learn how to use LLNL software in the cloud. Throughout August, join our tutorials on how to install and use several projects on AWS EC2 instances. No previous experience necessary.

Anna Maria Bailey, LLNL’s Chief Engineer for HPC and a Distinguished Member of Technical Staff, has enjoyed her “many careers” at the Lab and the ability to jump around to follow her interests.

A research team from Oak Ridge and Lawrence Livermore national labs won the first IPDPS Best Open-Source Contribution Award for the paper “UnifyFS: A User-level Shared File System for Unified Access to Distributed Local Storage.”

LLNL CTO Bronis de Supinski talks about how the Lab deploys novel architecture AI machines and provides an update on El Capitan.

Splitting memory resources in high performance computing between local nodes and a larger shared remote pool can help better support diverse applications.

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.

Lori Diachin will take over as director of the DOE’s Exascale Computing Project on June 1, guiding the successful, multi-institutional high performance computing effort through its final stages.

Livermore CTO Bronis de Supinski joins the Let's Talk Exascale podcast to discuss the details of LLNL's upcoming exascale supercomputer.

Variorum provides robust, portable interfaces that allow us to measure and optimize computation at the physical level: temperature, cycles, energy, and power. With that foundation, we can get the best possible use of our world-class computing resources.

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.

Updating a compiler can affect how code runs, leading to inconsistencies in outputs and creating problems for scientists. A new tool automatically finds the sources of these inconsistencies.