short-paper

Energy and Performance Analysis of Parallel Particle Solvers from the ScaFaCoS Library

Authors:

Michael Hofmann,

Gudula RüngerAuthors Info & Claims

ICPE '18: Proceedings of the 2018 ACM/SPEC International Conference on Performance Engineering

Pages 88 - 95

https://doi.org/10.1145/3184407.3184409

Published: 30 March 2018 Publication History

Abstract

Performance analysis in high performance computing (HPC) has traditionally focused on improving application programs, for example, by decreasing the overall runtime or increasing the throughput of floating point operations. However, the same approaches might also be used to influence the energy behavior. Since the increasing energy consumption of HPC platforms is gaining more and more attention, the identification of applications and platforms for which energy and performance measurement lead to differing results is of great importance. In this article, we analyze the energy and performance behavior of particle solvers from the ScaFaCoS library. Four different criteria are investigated with respect to their influence on the energy consumption and achieved performance. These criteria are the solution method chosen, the parameters of the solution method, the degree of parallelism, and the parameters of the hardware platform.

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Cited By

Kalinnik NKiesel RRauber TRichter MRünger G(2020)A performance- and energy-oriented extended tuning process for time-step-based scientific applicationsThe Journal of Supercomputing10.1007/s11227-020-03402-yOnline publication date: 25-Aug-2020
https://doi.org/10.1007/s11227-020-03402-y
Rauber TRunger G(2019)Multiprocessor Task Programming and Flexible Load Balancing for Time-Stepping Methods on Heterogeneous Cloud Infrastructures2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00277(1537-1544)Online publication date: Aug-2019
https://doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00277

Index Terms

Energy and Performance Analysis of Parallel Particle Solvers from the ScaFaCoS Library
1. Computing methodologies
  1. Parallel computing methodologies
    1. Parallel algorithms

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Information

Published In

cover image ACM Conferences

ICPE '18: Proceedings of the 2018 ACM/SPEC International Conference on Performance Engineering

March 2018

328 pages

ISBN:9781450350952

DOI:10.1145/3184407

General Chairs:
Katinka Wolter
Free University of Berlin, Germany
,
Will Knottenbelt
Imperial College London, UK
,
Program Chairs:
André van Hoorn
University of Stuttgart, Germany
,
Manoj Nambiar
Tata Consultancy Services, India
,
Heiko Koziolek
ABB, Germany

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 30 March 2018

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German Ministry of Science and Education (BMBF)

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ICPE '18

Sponsor:

ICPE '18: ACM/SPEC International Conference on Performance Engineering

April 9 - 13, 2018

Berlin, Germany

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Overall Acceptance Rate 252 of 851 submissions, 30%

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Cited By

Kalinnik NKiesel RRauber TRichter MRünger G(2020)A performance- and energy-oriented extended tuning process for time-step-based scientific applicationsThe Journal of Supercomputing10.1007/s11227-020-03402-yOnline publication date: 25-Aug-2020
https://doi.org/10.1007/s11227-020-03402-y
Rauber TRunger G(2019)Multiprocessor Task Programming and Flexible Load Balancing for Time-Stepping Methods on Heterogeneous Cloud Infrastructures2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00277(1537-1544)Online publication date: Aug-2019
https://doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00277

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