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Rollback sometimes works...if filtered
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Source Winter Simulation Conference archive
Proceedings of the 21st conference on Winter simulation table of contents
Washington, D.C., United States
Pages: 630 - 639  
Year of Publication: 1989
ISBN:0-911801-58-8
Authors
Sponsors
IIE : Institute of Industrial Engineers
NIST : National Institue of Standards & Technology
SES : SES
TIMS/CS :
IEEE-CS : Computer Society
ORSA : Operations Research Society of America
SIGSIM: ACM Special Interest Group on Simulation and Modeling
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 5,   Downloads (12 Months): 14,   Citation Count: 38
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ABSTRACT

We introduce a new parallel discrete event simulation algorithm called filtered rollback. It is a combination of the Time Warp and bounded lag simulation algorithms introduced previously. The "filter" postpones event processing in some subsystems in favor of safer simulation. The filter may be tuned by the simulationist; at one extreme the algorithm is conservative, i.e., free from rollback, and at the other extreme the algorithm is purely optimistic, i.e., relying exclusively on rollback. We prove that rollback cascading, wherein a "chain reaction" of secondary and higher generation rollbacks appear in the simulation, can be bounded by an appropriate tuning. The tuning achieves a trade-off between the two extremes which yields an efficient and scalable algorithm. Our method of proof uses a representation of the rollback cascading as a tree and models such a tree as a Galton-Watson branching process on which an additional structure is defined, a random walk with a barrier.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Asmussen, S. and Hering, H., Branching Processes, Birkhauser, 1983.
 
2
Chernoff, H., A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations. Ann. Math. Statist., 23 (1952), 494--507.
 
3
Gafni, A., Berry, O., Jefferson, D. Optimized virtual synchronization, Proc. 2nd Int. Workshop on Applied Math. and Performance/Reliability Models, Univ. of Rome II (1987), 229--244.
 
4
Jefferson, D. R., Virtual time. ACM Transactions on Programming Languages and Systems, 7, 3 (1985), 404--425.
 
5
Lubachevsky, B. D. Bounded lag distributed discrete event simulation (Extended Abstract), in Distributed Simulation, B. Unger, and D. Jefferson (eds.), SCS, Simulation Series, 19, 3 (1988), 183--192.
 
6
Lubachevsky, B. D. Efficient distributed event driven simulations of multiple-loop networks, Communications of the ACM, 32, 1 (1989), pp. 111--131.
 
7
Lubachevsky, B. D. Scalability of the bounded lag distributed discrete event simulation, in Distributed Simulation, B. Unger, and R. Fujimoto (eds.), SCS, Simulation Series, 21, 2 (1989), 100--107.
 
8
Sokol, L. M., Briscoe, D. P, and Wieland, A. P. MTW: a strategy for scheduling discrete simulation events for concurrent execution, in Distributed Simulation, B. Unger, and D. Jefferson (eds.), Simulation Series, SCS, 19, 3 (1988) 34--42.

CITED BY  38

Collaborative Colleagues:
B. Lubachevsky: colleagues
A. Shwartz: colleagues
A. Weiss: colleagues