Derived Field Generation
Livermore computer scientists have helped create a flexible framework that aids programmers in creating source code that can be used effectively on multiple hardware architectures.
Machine Learning
LLNL computer scientists use machine learning to model and characterize the performance and ultimately accelerate the development of adaptive applications.
InfiniBand
Livermore Computing staff is enhancing the high-speed InfiniBand data network used in many of its high performance computing and file systems.
LLNL and SambaNova Systems announce additional AI hardware to support Lab’s cognitive simulation efforts
The addition of the spatial data flow accelerator into LLNL’s Livermore Computing Center is part of an effort to upgrade the Lab’s cognitive simulation (CogSim) program.
National lab uses Elastic to optimize performance of projected world's fastest supercomputer
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.
Best paper winner finds the sources of calculation inconsistencies
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.