Scalable, Performance-Portable Particle-in-Cell Simulations and PByte-Scale Data-Challenges

We present the architecture, abstractions, novel developments, and workflows that enable high-resolution, fast turn-around computations on contemporary, leadership-scale supercomputers powered by both GPUs and CPUs from various vendors and on top of a generalized programming model (Alpaka). From the experience developing the open-source community code PIConGPU, strategies for handling PByte-scale data flows from thousands of computing devices for analysis with in situ processing and open data formats (openPMD) are presented. Furthermore, simulation control via a lightweight Python Jupyter interface as well as recent research towards just-in-time kernel generation for C++ with Cling-CUDA are shown as a mean for fast turn-around, close-to-experiment simulations.