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Making parallel simulations go fast
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Source Winter Simulation Conference archive
Proceedings of the 24th conference on Winter simulation table of contents
Arlington, Virginia, United States
Pages: 646 - 656  
Year of Publication: 1992
ISBN:0-7803-0798-4
Authors
Sponsors
ASA : American Statistical Association
NIST : National Institue of Standards & Technology
IEEE-CS : Computer Society
IEEE-SMCS : Systems, Man & Cybernetics Society
ACM: Association for Computing Machinery
ORSA : Operations Research Society of America
SIGSIM: ACM Special Interest Group on Simulation and Modeling
TIMS :
IIE : Institute of Industrial Engineers
SCS : Society for Computer Simulation
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 5,   Downloads (12 Months): 12,   Citation Count: 2
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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
Abrams, M. and Richardson, D. 1991. Implementing a Global Termination Condition and Collecting Output Measures in Parallel Simulation. In Proceedings of the SCS Multiconference on Advances in Parallel and Distributed Simulation, 86-91. Anaheim, California.
 
2
BeUenot, S. 1990. Global Virtual Time Algori~tms. In Proceedings of the SCS Multiconference on Distributed Simulation, 122-127. San Diego, California.
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Concepcion, A. I. and Kelly, S. G. 1991. Computing Global Virtual Time Using the Multi-Level Token Passing Algorithm. In Proceedings of the SCS Multiconference on Advances in Parallel and Distributed Simulation, 63-68. Anaheim, California.
 
5
Crockett, T. W. and Knott, J. D. 1985. System Software for the Finite Element Machine. NASA Contractor Report 3870, NASA Langley, Hampton, Virginia.
 
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Felderman, R. E. and Kleinrock, L. 1990. Two Processor Time Warp Analysis: Capturing the Effects of Message Queueing and Rollback/State Saving Costs. Submitted to ACM TOMACS.
 
8
Felderman, R. E. and Kleinrock, L. 1992. Two Processor Conservative Simulation Analysis. In Proceedings of the 1992 Western Simulation MultiConf erence on Parallel and Distributed Simulation, 169-177. Newport Beach, California.
 
9
Filoque, J. M., Gautrin, E. and Pottier, B. 1991. Efficient Global Computations on a Processors Network with Programmable Logic. Report 1374, Institut National de Recherche en Informatique et en Anutomatique, France.
 
10
Fujimoto, R. M. 1987. Performance Measurements of Distributed Simulation Strategies. TR UUCS-87-026a, Computer Science Dept., University of Utah, Salt Lake City, Utah.
 
11
Fujimoto, R. M. 1988. Lookahead in Parallel Discrete Event Simulation. In Proceedings of the 1988 International Conference on Parallel Processing, 34- 41. University Park, Pennsylvania.
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13
 
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15
Intel Corporation. 1989. iPSC/2 Programmer's Reference Manual. Beaverton, Oregon: Intel Scientific Computers.
16
 
17
Jefferson, D. and Sowizral, H. 1985. Fast Concurrent Simulation Using the Time Warp Mechanism. In Proceedings of the Conference on Distributed Simulation, 63-69. San Diego, California.
 
18
Jordan, H. F., Scalabrin, M. and Calvert, W. 1979. A Comparison of Three Types of Multiprocessor Algorithms. In Proceedings of the 1979 International Conference on Parallel Processing, 231-238.
 
19
Lin, Y. B. and Lazowska, E. D. 1989. Determining the Global Virtual Time in a Distributed Simulation. TR 90-01-02, Dept. of Computer Science, University of Washington, Seattle, Washington.
 
20
Lubachevsky, B. D. 1988. Bounded Lag Distributed Discrete Event Simulation. In Proceedings of the SCS Multiconference on Distributed Simulation, 183-191. San Diego, California.
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PancereUa, C. M. 1992. Improving the Efficiency of a Framework for Parallel Simulations. In Proceedings of the 1992 Western Simulation MultiConference on Parallel and Distributed Simulation, 22-29. Newport Beach, Califomia.
 
23
Pfister, G. F., Brantley, W. C., George, D. A., et. al.. 1985. The IBM Research Parallel Prototype (RP3): introduction and Architecture. In Proceedings of the 1985 International Conference on Parallel Processing, 764-771. St. Charles, Illinois.
 
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Reynolds Jr., P. F. 1991. An Efficient FrameWork for Parallel Simulations. In Proceedings of the SCS Multiconference on Advances in Parallel and Distributed Simulation, 167-174. Anaheim, California.
 
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Reynolds Jr., P. F. 1992. An Efficient Framework for Parallel Simulations. To appear in International Journal on Computer Simulations.
 
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Sokol, L. M., Briscoe, D. P. and Wieland, A. P. 1988. MTW: A Strategy for Scheduling Discrete Simulation Events for Concurrent Execution. In Proceedings of the SCS Multiconference on Distributed Simulation, 34-42. San Diego, California.
 
31
Srinivasan, S. 1992. Modeling a Framework for Parallel Simulations. Master's Thesis, Dept. of Computer Science, University of Virginia, Charlottesville, Virginia.
 
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Sun Microsystems. 1990. SBus Specification B.0. Mountain View, California: Sun Microsystems, inc. Thinking Machines Corporation. 1992. The Connection Machine CM-5 Technical Summary. Cambridge, Massachusetts: Thinking Machines Corporation.


Collaborative Colleagues:
Paul F. Reynolds, Jr.: colleagues
Carmen M. Pancerella: colleagues
Sudhir Srinivasan: colleagues