Scalable plasma simulation with ELMFIRE using efficient data structures in MPI process communication

We describe the parallel full-f gyrokinetic particle-in-cell plasma simulation code ELMFIRE and the issue of solving a electrostatic potential from particle data distributed across several MPI (Message Passing Interface) processes. The potential is solved through a linear system with a strongly sparse matrix and ELMFIRE stores data of the estimated nonzero diagonals of the whole matrix in every MPI process, with low performance. We present three alternative more memory efficient structures for gathering the data while keeping only a local part of the matrix. We also demonstrate that these alternative structures improve scalability, thus enabling more MPI processes and a finer time and space scale than before without sacrificing performance.