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A Distributed Chunk Calculation Approach for Self-scheduling of Parallel Applications on Distributed-memory Systems
Type of publication
Peer-reviewed
Publikationsform
Original article (peer-reviewed)
Author
Eleliemy Ahmed, Ciorba Florina M.,
Project
Multilevel Scheduling in Large Scale High Performance Computers
Show all
Original article (peer-reviewed)
Journal
Journal of Computational Science (JOCS2021)
Volume (Issue)
5
Page(s)
101284
Title of proceedings
Journal of Computational Science (JOCS2021)
DOI
10.1016/j.jocs.2020.101284
Open Access
URL
http://doi.org/10.1016/j.jocs.2020.101284
Type of Open Access
Publisher (Gold Open Access)
Abstract
Loop scheduling techniques aim to achieve load-balanced executions of scientific applications. Dynamic loop self-scheduling (DLS) libraries for distributed-memory systems are typically MPI-based and employ a centralized chunk calculation approach (CCA) to assign variably-sized chunks of loop iterations. We present a distributed chunk calculation approach (DCA) that supports various types of DLS techniques. Using both CCA and DCA, twelve DLS techniques are implemented and evaluated in different CPU slowdown scenarios. The results show that the DLS techniques implemented using DCA outperform their corresponding ones implemented with CCA, especially in extreme system slowdown scenarios.
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