  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 for I/O
efficiency, including the highly efficient ADIOS2 interface. Next, we explore
advanced optimization techniques such as data compression, aggregation, and
Lustre file striping, achieving write throughput improvements while enhancing
data storage efficiency. Finally, we analyze the enhanced high-throughput
parallel I/O and storage capabilities achieved through the integration of
openPMD with rapid metadata extraction in BP4 format. Our study demonstrates
that the integration of openPMD and advanced I/O optimizations significantly
enhances BIT1's I/O performance and storage capabilities, successfully
introducing high throughput parallel I/O and surpassing the capabilities of
traditional file I/O.
