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pGVT: an algorithm for accurate GVT estimation

Published: 01 July 1994 Publication History

Abstract

The time warp mechanism uses memory space to save event and state information for rollback processing. As the simulation advances in time, old state and event information can be discarded and the memory space reclaimed. This reclamation process is called fossil collection and is guided by a global time value called Global Virtual Time (GVT). That is, GVT represents the greatest minimum time of the fully committed events (the time before which no rollback will occur). GVT is then used to establish a boundary for fossil collection. This paper presents a new algorithm for GVT estimation called pGVT. pGVT was designed to support accurate estimates of the actual GVT value and it operates in an environment where the communication subsystem does not support FIFO message delivery and where message delivery failure may occur. We show that pGVT correctly estimates GVT values and present some performance comparisons with other GVT algorithms.

Cited By

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  • (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
  • (2012)A use of matrix with GVT computation in optimistic time warp algorithm for parallel simulationProceedings of the 15th Communications and Networking Simulation Symposium10.5555/2331762.2331776(1-6)Online publication date: 26-Mar-2012
  • (2010)An Introduction to Distributed SimulationModeling and Simulation Fundamentals10.1002/9780470590621.ch11(373-402)Online publication date: 14-Jul-2010
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Xiao Zhonge

A global virtual time (GVT) estimation algorithm, called pGVT, is designed for time warp systems that operate in an environment where reliable and first in, first out message delivery is not guaranteed. As a result, pGVT relies on message acknowledgment. A central GVT manager process calculates GVT values from information reported by the local processes. The key issue that the author is trying to solve is accurate GVT estimation with minimum reports from the local processes. The idea is that the local processes decide for themselves when to report new GVT information, instead of asking the GVT manager. A statistical method is used to assist the local processes in deciding. The method uses two statistical values. One is the average GVT increment for the last k increases of the GVT , D GVT , and the other is the ratio of the time for a message to be sent and acknowledged to the GVT manager and the average time between successive GVT broadcasts. A local process reports its local GVT LGVT <__?__Pub Caret> only when a straggler message is received or the last broadcast GVT approaches the current LGVT , that is, whenever <__?__Pub Fmt nolinebreak> GVT+K* D GVT ?LGVT <__?__Pub Fmt /nolinebreak> holds. Effectively, only those local processes that are executing on or near the critical path will report to the GVT manager.

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cover image ACM Conferences
PADS '94: Proceedings of the eighth workshop on Parallel and distributed simulation
August 1994
196 pages
ISBN:1565550277
DOI:10.1145/182478

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 July 1994

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8PADS94
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8PADS94: ACM/IEEE 8th Workshop on Parallel and Distributed
July 6 - 8, 1994
Edinburgh, Scotland, United Kingdom

Acceptance Rates

PADS '94 Paper Acceptance Rate 27 of 66 submissions, 41%;
Overall Acceptance Rate 398 of 779 submissions, 51%

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Cited By

View all
  • (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
  • (2012)A use of matrix with GVT computation in optimistic time warp algorithm for parallel simulationProceedings of the 15th Communications and Networking Simulation Symposium10.5555/2331762.2331776(1-6)Online publication date: 26-Mar-2012
  • (2010)An Introduction to Distributed SimulationModeling and Simulation Fundamentals10.1002/9780470590621.ch11(373-402)Online publication date: 14-Jul-2010
  • (2006)Causality information and fossil collection in timewarp simulationsProceedings of the 38th conference on Winter simulation10.5555/1218112.1218294(987-994)Online publication date: 3-Dec-2006
  • (2006)Causality Information and Fossil Collection in Time Warp SimulationsProceedings of the 2006 Winter Simulation Conference10.1109/WSC.2006.323186(987-994)Online publication date: Dec-2006
  • (2006)A formal framework for specifying and verifying time warp optimizationsParallel and Distributed Processing10.1007/BFb0098005(1228-1242)Online publication date: 28-Oct-2006
  • (2006)OFC: A distributed fossil-collection algorithm for Time-WarpDistributed Computing10.1007/BFb0056498(408-418)Online publication date: 2-Jun-2006
  • (2005)DSIMProceedings of the 37th conference on Winter simulation10.5555/1162708.1162771(346-355)Online publication date: 4-Dec-2005
  • (2005)DSIM: Scaling Time Warp to 1,033 ProcessorsProceedings of the Winter Simulation Conference, 2005.10.1109/WSC.2005.1574269(346-355)Online publication date: 2005
  • (2005)Seven-O'ClockProceedings of the 19th Workshop on Principles of Advanced and Distributed Simulation10.1109/PADS.2005.27(39-48)Online publication date: 1-Jun-2005
  • Show More Cited By

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