Article

A Multi-State Q-Learning Approach for the Dynamic Load Balancing of Time Warp

Authors:

Carl TropperAuthors Info & Claims

PADS '10: Proceedings of the 2010 IEEE Workshop on Principles of Advanced and Distributed Simulation

Pages 142 - 149

https://doi.org/10.1109/PADS.2010.5471661

Published: 17 May 2010 Publication History

Abstract

In this paper, we present a dynamic load-balancing algorithm for optimistic gate level simulation making use of a machine learning approach. We first introduce two dynamic load-balancing algorithms oriented towards balancing the computational and communication load respectively in a Time Warp simulator. In addition, we utilize a multi-state Q-learning approach to create an algorithm which is a combination of the first two algorithms. The Q-learning algorithm determines the value of three important parameters- the number of processors which participate in the algorithm, the load which is exchanged during its execution and the type of load-balancing algorithm. We investigate the algorithm on gate level simulations of several open source VLSI circuits.

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Cited By

Marotta RMontesano FQuaglia F(2023)Effective Access to the Committed Global State in Speculative Parallel Discrete Event Simulation on Multi-core MachinesProceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation10.1145/3573900.3591117(107-117)Online publication date: 21-Jun-2023
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Helms TReinhardt OUhrmacher ADiallo STolk A(2015)Bayesian changepoint detection for generic adaptive simulation algorithmsProceedings of the 48th Annual Simulation Symposium10.5555/2876341.2876350(62-69)Online publication date: 12-Apr-2015
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de Carvalho EJunqueira MMoreira ECarpinteiro ODe Rango FRisco Martín JCetinkaya D(2015)An analysis on the metrics for dynamic process scheduling on distributed simulation using optimistic protocolsProceedings of the Conference on Summer Computer Simulation10.5555/2874916.2874958(1-8)Online publication date: 26-Jul-2015
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cover image ACM Conferences

PADS '10: Proceedings of the 2010 IEEE Workshop on Principles of Advanced and Distributed Simulation

May 2010

164 pages

ISBN:9781424472925

Sponsors

SIGSIM: ACM Special Interest Group on Simulation and Modeling

Publisher

IEEE Computer Society

United States

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Published: 17 May 2010

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Cited By

Marotta RMontesano FQuaglia F(2023)Effective Access to the Committed Global State in Speculative Parallel Discrete Event Simulation on Multi-core MachinesProceedings of the 2023 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation10.1145/3573900.3591117(107-117)Online publication date: 21-Jun-2023
https://dl.acm.org/doi/10.1145/3573900.3591117
Helms TReinhardt OUhrmacher ADiallo STolk A(2015)Bayesian changepoint detection for generic adaptive simulation algorithmsProceedings of the 48th Annual Simulation Symposium10.5555/2876341.2876350(62-69)Online publication date: 12-Apr-2015
https://dl.acm.org/doi/10.5555/2876341.2876350
de Carvalho EJunqueira MMoreira ECarpinteiro ODe Rango FRisco Martín JCetinkaya D(2015)An analysis on the metrics for dynamic process scheduling on distributed simulation using optimistic protocolsProceedings of the Conference on Summer Computer Simulation10.5555/2874916.2874958(1-8)Online publication date: 26-Jul-2015
https://dl.acm.org/doi/10.5555/2874916.2874958
Solar RGil-Costa VMarin MDe Rango FRisco Martín JCetinkaya D(2015)Dynamic load balance for approximate parallel simulations with consistent hashingProceedings of the Conference on Summer Computer Simulation10.5555/2874916.2874934(1-10)Online publication date: 26-Jul-2015
https://dl.acm.org/doi/10.5555/2874916.2874934
Helms TEwald RRybacki SUhrmacher A(2015)Automatic Runtime Adaptation for Component-Based Simulation AlgorithmsACM Transactions on Modeling and Computer Simulation10.1145/282150926:1(1-24)Online publication date: 19-Oct-2015
https://dl.acm.org/doi/10.1145/2821509
Wienß JStein MEwald RHimmelspach JVanmechelen KCai W(2013)Evaluating simulation software components with player rating systemsProceedings of the 6th International ICST Conference on Simulation Tools and Techniques10.5555/2512734.2512740(41-50)Online publication date: 5-Mar-2013
https://dl.acm.org/doi/10.5555/2512734.2512740
Helms TEwald RRybacki SUhrmacher ALoper MWainer G(2013)A generic adaptive simulation algorithm for component-based simulation systemsProceedings of the 1st ACM SIGSIM Conference on Principles of Advanced Discrete Simulation10.1145/2486092.2486095(11-22)Online publication date: 19-May-2013
https://dl.acm.org/doi/10.1145/2486092.2486095
Vitali RPellegrini AQuaglia F(2012)Towards Symmetric Multi-threaded Optimistic Simulation KernelsProceedings of the 2012 ACM/IEEE/SCS 26th Workshop on Principles of Advanced and Distributed Simulation10.1109/PADS.2012.46(211-220)Online publication date: 15-Jul-2012
https://dl.acm.org/doi/10.1109/PADS.2012.46
Peluso SDidona DQuaglia F(2011)Application Transparent Migration of Simulation Objects with Generic Memory LayoutProceedings of the 2011 IEEE Workshop on Principles of Advanced and Distributed Simulation10.1109/PADS.2011.5936755(1-9)Online publication date: 14-Jun-2011
https://dl.acm.org/doi/10.1109/PADS.2011.5936755
Chen LLu YYao YPeng SWu L(2011)A Well-Balanced Time Warp System on Multi-Core EnvironmentsProceedings of the 2011 IEEE Workshop on Principles of Advanced and Distributed Simulation10.1109/PADS.2011.5936752(1-9)Online publication date: 14-Jun-2011
https://dl.acm.org/doi/10.1109/PADS.2011.5936752

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