LLNL participates in the ISC High Performance Conference (ISC22) on May 29 through June 2.
LLNL’s Python 3–based ATS tool provides scientific code teams with automated regression testing across HPC architectures.
Highlights include scalable deep learning, high-order finite elements, data race detection, and reduced order models.
Highlights include perspectives on machine learning and artificial intelligence in science, data driven models, autonomous vehicle operations, and the OpenMP standard 5.0.
Highlights include CASC director Jeff Hittinger's vision for the center as well as recent work with PruneJuice DataRaceBench, Caliper, and SUNDIALS.
The PRUNERS Toolset offers four novel debugging and testing tools to assist programmers with detecting, remediating, and preventing errors in a coordinated manner.
LLNL’s Stack Trace Analysis Tool helps users quickly identify errors in code running on today’s largest machines.
Caliper enables users to build customized performance measurement and analysis solutions by connecting independent context annotations, measurement services, and data processing services.
This tool that automatically diagnoses performance and correctness faults in MPI applications. It identifies abnormal MPI tasks and code regions and finds the least-progressed task.
Greg Lee helps develop tools designed to boost performance and productivity of Livermore scientists.