LOCAL
This project's techniques reduce bandwidth requirements for large unstructured data by making use of data compression and optimizing the layout of the data for better locality and cache reuse.
STAT
LLNL’s Stack Trace Analysis Tool helps users quickly identify errors in code running on today’s largest machines.
TOSS
Researchers are developing a standardized and optimized operating system and software for deployment across Linux clusters to enable HPC at a reduced cost.
UnifyFS team wins IPDPS award for open-source software
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.”
Talking novel architectures and El Capitan with Lawrence Livermore
LLNL CTO Bronis de Supinski talks about how the Lab deploys novel architecture AI machines and provides an update on El Capitan.
Investigation of disaggregated memory systems wins poster award
Splitting memory resources in high performance computing between local nodes and a larger shared remote pool can help better support diverse applications.