In the project's first year, we identified and detailed the scientific grand challenges and associated use cases. In particular, we defined the figure of merit for each code in order to enable the solution of the challenge. These figures will allow us to monitor the progress of each grand challenge during the project. In addition, we established a performance baseline for parallel scaling, I/O performance, and accelerator usage to compare the new developments in the project. The progress towards this objective is detailed in deliverables D1.1–D1.8. We assessed parallel scalability and efficiency on different EuroHPC systems and clusters available in the consortium to provide an initial baseline for current development. We secured access to all the EuroHPC systems. We identified the necessary steps for enabling algorithmic advancements in the application, including load balancing, data compression, resilience, I/O, and portable programming systems (MPI, Alpaka). This work is detailed in D3.1 D4.1 and D5.1. We ensured that each Plasma-PEPSC developer is committed to following modern software engineering practices, including continuous integration and automated deployment on EuroHPC systems. All Plasma-PEPSC codes are now available as open-source software through various licensing schemes and remote repositories.
During the second reporting period, Plasma-PEPSC delivered twelve deliverables and closed nine milestones, making progress from software readiness to co-design and dissemination. WP1 released the first consolidated set of plasma simulation codes with documentation at M24 and, by M30, provided updated performance assessments and refined scientific challenges for all four flagship applications- BIT1, GENE, PIConGPU, and Vlasiator, capturing both code evolution and scientific priorities. WP2 completed Phase-1 co-design on the European Processor Initiative stack and documented experiences with ARM and RISC-V, then reported initial Phase-2 results on the SiPearl ARM processor and the RISC-V accelerator. WP3 advanced algorithmic and library work across the suite, reporting improvements in MPI features, dynamic load-balancing, and resilience. WP4 progressed with parallel I/O, in-situ workflows, and compression schemes, while WP5 detailed the algorithmic changes and memory optimizations needed to run efficiently on accelerated and heterogeneous nodes. WP6 refreshed the dissemination, training, collaboration, and exploitation plan and documented community-building activities, and WP7 issued an updated Data Management Plan.
