Enabling High-Throughput Parallel I/O in Particle-in-Cell Monte Carlo Simulations with openPMD and Darshan I/O Monitoring
Jeremy J. Williams, Daniel Medeiros, Stefan Costea, David Tskhakaya,, Franz Poeschel, Ren\'e Widera, Axel Huebl, Scott Klasky, Norbert Podhorszki,, Leon Kos, Ales Podolnik, Jakub Hromadka, Tapish Narwal, Klaus Steiniger,, Michael Bussmann, Erwin Laure, Stefano Markidis

TL;DR
This paper enhances parallel I/O performance in Particle-in-Cell Monte Carlo plasma simulations by integrating openPMD, optimizing I/O techniques, and employing advanced storage strategies, significantly reducing bottlenecks in large-scale HPC environments.
Contribution
It introduces an openPMD-based I/O adaptor with optimized techniques for high-throughput parallel I/O in PIC MC simulations, surpassing traditional methods.
Findings
Achieved significant I/O throughput improvements.
Demonstrated effective data compression and aggregation.
Enhanced storage efficiency with Lustre file striping.
Abstract
Large-scale HPC simulations of plasma dynamics in fusion devices require efficient parallel I/O to avoid slowing down the simulation and to enable the post-processing of critical information. Such complex simulations lacking parallel I/O capabilities may encounter performance bottlenecks, hindering their effectiveness in data-intensive computing tasks. In this work, we focus on introducing and enhancing the efficiency of parallel I/O operations in Particle-in-Cell Monte Carlo simulations. We first evaluate the scalability of BIT1, a massively-parallel electrostatic PIC MC code, determining its initial write throughput capabilities and performance bottlenecks using an HPC I/O performance monitoring tool, Darshan. We design and develop an adaptor to the openPMD I/O interface that allows us to stream PIC particle and field information to I/O using the BP4 backend, aggressively optimized…
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