Parallel Software Development Tools
We’re working on a new generation of tools to help our users with exascale machine bottlenecks. Our research emphasizes performance analysis and code correctness and aims to address these main challenges: seamless integration with programming models, scalability, automatic analysis, detection of inefficient resource usage, and tool modularity. View content related to Parallel Software Development Tools.
Although in-person conferences are not feasible this summer, Lawrence Livermore will participate in the online ISC High Performance Conference (ISC20) on June 22–25. The event brings together the HPC community—from research centers, commercial companies, academia, national laboratories, government agencies, exhibitors, and more—to share the latest technology of interest to HPC developers and users.
LLNL’s new Maestro Workflow Conductor—a lightweight, open-source Python tool that can launch multi-step software simulation workflows in a clear, concise, consistent, and repeatable manner—is helping scientists develop sustainable computational workflows in an array of disciplines ranging from machine learning to molecular dynamics, cancer, and cardiac research.