The Supercomputing conference holds a student cluster competition - A competition that aims to introduce undergraduate students to the world of High Performance Computing. One of the tasks at the SC19 conference was to reproduce the scaling results obtained in the article titled Computing Planetary Interior Normal Modes with a Highly Parallel Polynomial Filtering Eigensolver by Jia Shi et al. They introduced a new approach to the problem of calculating planetary normal modes. The developed method is a highly parallel algorithm that approximates the results via the mixed finite element method on unstructured tetrahedral meshes. The cluster used consisted of five 40-core Intel Xeon Cascade Lake nodes, equipped with 384 GB of RAM each. The original study was demonstrated on Stampede2 system on partitions ranging from 2 to 256 nodes with 48-core Intel Xeon Skylake and 192 GB of RAM each. Our cluster was equipped with Infiniband interconnect while Stampede2 used Intel Omni-Path network. We decided to work with HPC-X MPI library in place of Intel MPI used the reference study. The design - sizes and schedule - of experimental runs was the most challenging part of our study. We run both strong and weak scalability experiments in a one set of runs in order to fit in limited computing capacity and very tight time schedule. Due to limitations of our hardware, we had to split the weak scaling study into two separate smaller studies. We didn't manage to reproduce the exact results, however, we achieved similar scalability trend.