Critique of "Planetary Normal Mode Computation: Parallel Algorithms, Performance, and Reproducibility" 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 article "Computing Planetary Interior Normal Modes with a Highly Parallel Polynomial Filtering Eigensolver", by J. Shi et al. , which describes a highly parallel algorithm...

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Published in:IEEE transactions on parallel and distributed systems Vol. 32; no. 11; pp. 2639 - 2642
Main Authors: Liu, David, Cinnamon, Matthew, Garvin, Thorne, Karavanov, Andrei, Park, Sungchan, Strobeck, Darius, Lumsdaine, Andrew
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Clusters
Competition
Computation
Computational modeling
Eigenvalues and eigenfunctions
Mars
Planetary interiors
Polynomials
Reproducibility
Reproducible computation
Runtime
Scalability
Software
Solids
student cluster competition
ISSN:1045-9219, 1558-2183
Online Access:Get full text
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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.
AbstractList 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.
Author Garvin, Thorne
Cinnamon, Matthew
Park, Sungchan
Lumsdaine, Andrew
Strobeck, Darius
Liu, David
Karavanov, Andrei
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SubjectTerms Algorithms
Clusters
Competition
Computation
Computational modeling
Eigenvalues and eigenfunctions
Mars
Planetary interiors
Polynomials
Reproducibility
Reproducible computation
Runtime
Scalability
Software
Solids
student cluster competition
Title Critique of "Planetary Normal Mode Computation: Parallel Algorithms, Performance, and Reproducibility" by SCC Team From University of Washington
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