Critique of 'Planetary Normal Mode Computation: Parallel Algorithms, Performance, and Reproducibility' by SCC Team from University of Washington

  • David Liu
  • , Matthew Cinnamon
  • , Thorne Garvin
  • , Andrei Karavanov
  • , Sungchan Park
  • , Darius Strobeck
  • , Andrew Lumsdaine

Research output: Contribution to journalArticlepeer-review

Abstract

One of the tasks for the SC19 Student Cluster Competition is to reproduce the results in the reproducibility challenge article '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 article, 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.

Original languageEnglish
Article number9325093
Pages (from-to)2639-2642
Number of pages4
JournalIEEE Transactions on Parallel and Distributed Systems
Volume32
Issue number11
DOIs
StatePublished - Nov 1 2021

Keywords

  • Reproducible computation
  • student cluster competition

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