FEPAC: A framework for evaluating parallel algorithms on cluster architectures

Mehul Warade, Jean-Guy Schneider, Kevin Lee

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

6 Citations (Scopus)

Abstract

For many years, computer scientists have explored the computing power of so-called computing clusters to address performance requirements of computationally intensive tasks. Historically, computing clusters have been optimized with run-time performance in mind, but increasingly energy consumption has emerged as a second dimension that needs to be considered when optimizing cluster configurations. However, there is a lack of generally available tool support to experiment with cluster and algorithm configurations in order to identify "sweet-spots"with regards to both, run-time performance and energy consumption, respectively. In this work, we are introducing FEPAC, a framework for the automated evaluation of parallel algorithms on different cluster architectures and different deployments of software processes to hardware nodes, allowing users to explore the impact of different configurations on run-time properties of their computations. As proof of concept, the utility of the framework is demonstrated on a custom-built Raspberry Pi 3B+ cluster using different types of parallel algorithms as benchmarks. The experiments evaluate matrix multiplication, kmeans, and OpenCV on varying sizes of cluster, and showed that although a larger cluster improves performance, there is often a trade-off between energy and computation time.

Original languageEnglish
Title of host publicationProceedings of the Australasian Computer Science Week Multiconference 2021 (ACSW 2021)
EditorsNigel Stanger, Veronica Liesaputra Joachim
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages10
ISBN (Electronic)9781450389563
DOIs
Publication statusPublished - 2021
Externally publishedYes
EventAustralasian Symposium on Parallel and Distributed Computing 2021 - Online, New Zealand
Duration: 1 Feb 20215 Feb 2021
https://sites.google.com/monash.edu/auspdc2021/etusivu (Website)
https://dl-acm-org.ezproxy.lib.monash.edu.au/action/showFmPdf?doi=10.1145%2F3437378 (Proceedings)

Conference

ConferenceAustralasian Symposium on Parallel and Distributed Computing 2021
Abbreviated titleAusPDC 2021
Country/TerritoryNew Zealand
Period1/02/215/02/21
Internet address

Keywords

  • Cluster Computing
  • Energy-Aware
  • Evaluation Framework
  • Parallel Algorithms
  • Single Board Computers

Cite this