Memory-Efficient Optimization of Gyrokinetic Particle-to-Grid Interpolation for Multicore Processors

We present multicore parallelization strategies for the particle-to-grid interpolation step in the Gyrokinetic Toroidal Code (GTC), a 3D particle-in-cell (PIC) application to study tur-bulent transport in magnetic-confinement fusion devices. Particle-grid interpolation is a known performance bottleneck in sev-eral PIC applications. In GTC, this step involves particles depositing charges to a 3D toroidal mesh, and multiple par-ticles may contribute to the charge at a grid point. We de-sign new parallel algorithms for the GTC charge deposition kernel, and analyze their performance on three leading mul-ticore platforms. We implement thirteen different variants for this kernel and identify the best-performing ones given typical PIC parameters such as the grid size, number of par-ticles per cell, and the GTC-specific particle Larmor radius variation. We find that our best strategies can be 2 × faster than the reference optimized MPI implementation, and can substantially reduce the MPI memory footprint. Our anal-ysis provides insight into desirable architectural features for high-performance PIC simulation codes. 1