Asynchronous simulated annealing on the placement problem: A beneficial race condition
Asynchronous simulated annealing on the placement problem: A beneficial race condition
Race conditions, which occur when compute workers do not synchronise correctly, are considered undesirable in parallel computing, as they introduce often-unintended stochastic behaviour. This study presents an asynchronous parallel algorithm with a race condition, and demonstrates that it reaches a superior solution faster than the equivalent synchronous algorithm without the race condition. Specifically, a parallel simulated annealing algorithm that solves a graph mapping problem (placement) is used to explore this. This paper illustrates how problem size and degree of parallelism affects both the collision rate caused by the race condition, and convergence time. The asynchronous approach reaches a superior solution in half the time of the equivalent synchronous approach. The solver presented here can be applied to application deployment in distributed systems, and the concept can be applied to problems solvable by global optimisation methods, where fitness errors can be tolerated in exchange for faster execution.
High performance computing, Optimization, Parallel computing, Place and route, Simulated annealing
242-251
Vousden, Mark
72f20dc7-d350-4982-a680-2d1f9ed5f07f
Bragg, Graeme M.
b5fd19b9-1a51-470b-a226-2d4dd5ff447a
Brown, Andrew D.
5c19e523-65ec-499b-9e7c-91522017d7e0
November 2022
Vousden, Mark
72f20dc7-d350-4982-a680-2d1f9ed5f07f
Bragg, Graeme M.
b5fd19b9-1a51-470b-a226-2d4dd5ff447a
Brown, Andrew D.
5c19e523-65ec-499b-9e7c-91522017d7e0
Vousden, Mark, Bragg, Graeme M. and Brown, Andrew D.
(2022)
Asynchronous simulated annealing on the placement problem: A beneficial race condition.
Journal of Parallel and Distributed Computing, 169, .
(doi:10.1016/j.jpdc.2022.07.001).
Abstract
Race conditions, which occur when compute workers do not synchronise correctly, are considered undesirable in parallel computing, as they introduce often-unintended stochastic behaviour. This study presents an asynchronous parallel algorithm with a race condition, and demonstrates that it reaches a superior solution faster than the equivalent synchronous algorithm without the race condition. Specifically, a parallel simulated annealing algorithm that solves a graph mapping problem (placement) is used to explore this. This paper illustrates how problem size and degree of parallelism affects both the collision rate caused by the race condition, and convergence time. The asynchronous approach reaches a superior solution in half the time of the equivalent synchronous approach. The solver presented here can be applied to application deployment in distributed systems, and the concept can be applied to problems solvable by global optimisation methods, where fitness errors can be tolerated in exchange for faster execution.
Text
1-s2.0-S0743731522001666-main
- Version of Record
More information
Accepted/In Press date: 7 July 2022
e-pub ahead of print date: 18 July 2022
Published date: November 2022
Additional Information:
Funding Information:
We acknowledge financial support from EPSRC ( EP/N031768/1 ).
Publisher Copyright:
© 2022 The Author(s)
Keywords:
High performance computing, Optimization, Parallel computing, Place and route, Simulated annealing
Identifiers
Local EPrints ID: 469023
URI: http://eprints.soton.ac.uk/id/eprint/469023
ISSN: 0743-7315
PURE UUID: c4a981c2-6dd2-4e2c-9c6b-0b7974c5257f
Catalogue record
Date deposited: 05 Sep 2022 16:46
Last modified: 18 Mar 2024 03:40
Export record
Altmetrics
Contributors
Author:
Mark Vousden
Author:
Graeme M. Bragg
Author:
Andrew D. Brown
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics