Critique of Computing Planetary Interior Normal Modes with a Highly Parallel Polynomial Filtering Eigensolver by SCC Team from University of Washington

One of the tasks for the SC19 Student Cluster Competition is to reproduce the results in the reproducibility challenge paper Computing Planetary Interior Normal Modes with a Highly Parallel Polynomial Filtering Eigensolver, by J. Shi et al., which describes a highly parallel algorithm for computing planetary normal modes. In running experiments from the paper, we study the weak and strong scalability of the algorithm, as well as the relationship between model size, degree of polynomial filter, and execution time. We investigate these findings on a two-node, 64-core Intel Skylake-based Xeon cluster. Unfortunately, we are able to confirm some, but not all, of the original findings, with discrepancies possibly due to a low number of experimental runs due to competition time limits as well as nonuniform scaling of compute resources.