Abstract
In this article we present our results from the SC19 Student Cluster Competition Reproducibility Challenge. The challenge entails reproducing the article entitled “Computing Planetary Interior Normal Modes with A Highly Parallel Polynomial Filtering Eigensolver” presented at SC'18, which proposes a parallel polynomial filtered Lanczos algorithm to directly calculate the planetary normal modes of heterogeneous planets. The proposed algorithm showed excellent performance with relatively low memory consumption and high parallel efficiency. In this work, we reproduce the scaling tests in that article on a cluster using Intel Cascade Lake architecture and use the proposed algorithm to illustrate specific normal modes of Mars. We compare the results obtained on our cluster with those in the original article. We also design a new metric to better analyze the results. In addition, we use the profiling tool Intel VTune Amplifier to explain our discoveries. Our results demonstrate that the given models show great scalability, which is similar to the original article. The required normal modes of Mars are also successfully calculated and visualized.
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