Exascale particle-in-cell (PIC) simulations like Vector Particle-In-Cell (VPIC) face critical parallel input/output (I/O) bottlenecks due to legacy proprietary formats and storage bloat from redundant ghost cells. We present two architectural contributions: a Kokkos-aware staging pipeline that eliminates ghost cell padding – yielding a 67% reduction in grid-based export sizes – and a parallel Hierarchical Data Format 5 (HDF5) backend validated against h5bench in a weak-scaling study up to 896 MPI ranks. Our pipelined architecture achieves file-per-process (FPP) throughput comparable to the legacy binary format, outpacing monolithic bulk-writing benchmarks while isolating collective I/O (CIO) synchronization overheads, establishing a definitive performance baseline for emerging Exascale architectures.

VPIC is a general purpose particle-in-cell simulation code for modeling plasma phenomena such as magnetic reconnection, fusion, solar weather, and laser-plasma interaction in three dimensions using large numbers of particles. VPIC's capacity in both fidelity and scale makes it particularly well-suited for plasma research on pre-exascale and exascale platforms. In this article, we demonstrate the unique challenges involved in preparing the VPIC code for operation at exascale, outlining important optimizations to make VPIC efficient on accelerators. Specifically, we show the work undertaken in adapting VPIC to exploit the portability-enabling framework Kokkos and highlight the enhancements to VPIC's modeling capabilities to achieve performance at exascale. We assess the achieved performance-portability trade-off through a suite of studies on nine different varieties of modern pre-exascale hardware. Our performance-portability study includes weak-scaling runs on three of the top ten TOP500 supercomputers, as well as a comparison of low-level system performance of hardware from four different vendors.