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.
What do Batman, a ukulele, and a popcorn machine have in common?
In the early hours of the morning on July 15, 2016, participants from around the Lab began to gather to continue their projects on the second day of Computation’s summer hackathon.
For 20 years, scientists from LLNL’s Center for Applied Scientific Computing (CASC) have contributed scientific research and development in mathematics, computer science, and data science that have directly impacted national security and advanced basic science.
Nikhil Jain has been named LLNL’s second Sidney Fernbach Postdoctoral Fellow, a highly competitive postdoctoral position awarded to candidates with exceptional talent in computer science.
Lawrence Livermore’s 2016 spring hackathon saw an all-time high of 68 people participate and matched last year’s spring high of 39 different projects.
Livermore researchers are blending performance analysis with information visualization to diagnose performance issues on increasingly complex machines.