Our Road to Exascale: Particle Accelerator & Laser-Plasma Modeling

The IDEAS Productivity project, in partnership with the DOE Computing Facilities of the ALCF, OLCF, and NERSC, and the DOE Exascale Computing Project (ECP), organizes the webinar series on Best Practices for HPC Software Developers.

As part of this series, we offer one-hour webinars on topics in scientific software development and high-performance computing, approximately once a month. The March webinar is titled Our Road to Exascale: Particle Accelerator & Laser-Plasma Modeling; and will be presented by Axel Huebl (Lawrence Berkeley National Laboratory). The webinar will take place on Wednesday, March 15, 2023, at 1:00 pm ET.

Abstract:

Particle accelerators, among the largest, most complex devices, demand increasingly sophisticated computational tools for the design and optimization of the next generation of accelerators that will meet the challenges of increasing energy, intensity, accuracy, compactness, complexity and efficiency. It is key that contemporary software take advantage of the latest advances in computer hardware and scientific software engineering practices, delivering speed, reproducibility and feature composability for the aforementioned challenges.

The webinar will discuss the experience of the developers of WarpX in the US DOE Exascale Computing Project (ECP), which led to the 2022 ACM Gordon Bell Prize. Including the first Exascale supercomputer Frontier, WarpX uses GPUs and CPUs at massive scale; research efforts have advanced particle-in-cell algorithms such as dynamic load balancing, block-structured mesh-refinement, and modern relativistic Maxwell solvers. The webinar will present strategies and results in performance portability. In particular, the webinar will discuss the team-of-teams approach for software co-design in AMReX, software architecture, quality assurance, developer & user productivity, and ecosystem interplay that has lifted up accelerator modeling activities to be fast, open, modular and sustainable over the long term.