Understanding the Impact of openPMD on BIT1, a Particle-in-Cell Monte Carlo Code, through Instrumentation, Monitoring, and In-Situ AnalysisShow others and affiliations
2024 (English)In: Euro-Par 2024: Parallel Processing Workshops: Euro-Par 2024 International Workshops, August 26–30, Madrid, Spain, 2024Conference paper, Published paper (Refereed)
Abstract [en]
Particle-in-Cell Monte Carlo simulations on large-scale systems play a fundamental role in understanding the complexities of plasma dynamics in fusion devices. Efficient handling and analysis of vast datasets are essential for advancing these simulations. Previously, we addressed this challenge by integrating openPMD with BIT1, a Particle-in-Cell Monte Carlo code, streamlining data streaming and storage. This integration not only enhanced data management but also improved write throughput and storage efficiency. In this work, we delve deeper into the impact of BIT1 openPMD BP4 instrumentation, monitoring, and in-situ analysis. Utilizing cutting-edge profiling and monitoring tools such as gprof, CrayPat, Cray Apprentice2, IPM, and Darshan, we dissect BIT1's performance post-integration, shedding light on computation, communication, and I/O operations. Fine-grained instrumentation offers insights into BIT1's runtime behavior, while immediate monitoring aids in understanding system dynamics and resource utilization patterns, facilitating proactive performance optimization. Advanced visualization techniques further enrich our understanding, enabling the optimization of BIT1 simulation workflows aimed at controlling plasma-material interfaces with improved data analysis and visualization at every checkpoint without causing any interruption to the simulation.
Place, publisher, year, edition, pages
2024.
Keywords [en]
Performance Monitoring and Analysis, openPMD, Parallel I/O, ADIOS2, gprof, CrayPat, Cray Apprentice2, IPM, Darshan, Distributed Storage, Efficient Data Processing, In-Situ Analysis, Large-Scale PIC Simulations
National Category
Fusion, Plasma and Space Physics Computer Systems Computer Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-351018OAI: oai:DiVA.org:kth-351018DiVA, id: diva2:1885836
Conference
30th International European Conference on Parallel and Distributed Computing
Note
QC 20240726
2024-07-252024-07-252024-08-15Bibliographically approved