NPSI adaptive synchronization algorithms for PDES

Adaptive approaches to synchronization in parallel discrete event simulations hold significant potential for performance improvement. We contend that an adaptive approach based on low cost near-perfect system state information is the most likely to yield a consistently efficient synchronization algorithm. We suggest a framework by which NPSI (near-perfect state information) adaptive protocols could be designed and describe the first such protocol-elastic time algorithm. We present performance results which show that NPSI protocols are very promising. In particular, they have the capacity to outperform time warp consistently in both time and space.

[1]  Anand R. Tripathi,et al.  Evaluation of a Local Adaptive Protocol for Distributed Discrete Event Simulation , 1994, 1994 International Conference on Parallel Processing Vol. 3.

[2]  Satish K. Tripathi,et al.  Parallel and distributed simulation of discrete event systems , 1994 .

[3]  Samir R Das,et al.  An adaptive memory management protocol for Time Warp parallel simulation , 1994, SIGMETRICS.

[4]  Yi-Bing Lin,et al.  Memory Management Algorithms for Optimistic Parallel Simulation , 1994, Inf. Sci..

[5]  Paul F. Reynolds,et al.  Non-Interfering Gvt Computation via Asynchronous Global Reductions , 1993, Proceedings of 1993 Winter Simulation Conference - (WSC '93).

[6]  Steven Bellenot,et al.  Performance of a riskfree Time Warp operating system , 1993, PADS '93.

[7]  Jeff S. Steinman,et al.  Breathing Time Warp , 1993, PADS '93.

[8]  Hassan Rajaei,et al.  The local Time Warp approach to parallel simulation , 1993, PADS '93.

[9]  Philip A. Wilsey,et al.  Adaptive bounded time windows in an optimistically synchronized simulator , 1993, [1993] Proceedings Third Great Lakes Symposium on VLSI-Design Automation of High Performance VLSI Systems.

[10]  Phillip M. Dickens,et al.  Analysis of the aggressive global windowing algorithm , 1993 .

[11]  Paul F. Reynolds,et al.  Making parallel simulations go fast , 1992, WSC '92.

[12]  David M. Nicol,et al.  State of the art in parallel simulation , 1992, WSC '92.

[13]  Atul Prakash,et al.  Filter: an algorithm for reducing cascaded rollbacks in optimistic distributed simulations , 1991, [1991] Proceedings of the 24th Annual Simulation Symposium.

[14]  J. Steinman.  Interactive SPEEDES , 1991, [1991] Proceedings of the 24th Annual Simulation Symposium.

[15]  Jeff McAffer,et al.  A unified distributed simulation system , 1990, 1990 Winter Simulation Conference Proceedings.

[16]  David M. Nicol,et al.  Performance bounds on parallel self-initiating discrete-event simulations , 1990, TOMC.

[17]  David M. Nicol,et al.  Optimal Dynamic Remapping of Data Parallel Computations , 1990, IEEE Trans. Computers.

[18]  R. M. Fujimoto,et al.  Parallel discrete event simulation , 1989, WSC '89.

[19]  Alan Weiss,et al.  Rollback Sometimes Works...If Filtered , 1989, 1989 Winter Simulation Conference Proceedings.

[20]  David R. Jefferson,et al.  Limitation Of Optimism In The Time Warp Operating System , 1989, 1989 Winter Simulation Conference Proceedings.

[21]  R. L. Gimarco.  Distributed simulation using hierarchical rollback , 1989, WSC '89.

[22]  Krithi Ramamritham,et al.  Distributed Scheduling of Tasks with Deadlines and Resource Requirements , 1989, IEEE Trans. Computers.

[23]  J. Walrand,et al.  WOLF: A rollback algorithm for optimistic distributed simulation systems , 1988, 1988 Winter Simulation Conference Proceedings.

[24]  P. Reynolds.  A spectrum of options for parallel simulation , 1988, 1988 Winter Simulation Conference Proceedings.

[25]  Domenico Ferrari,et al.  An Empirical Investigation of Load Indices for Load Balancing Applications , 1987, Performance.

[26]  David M. Nicol,et al.  Optimal dynamic remapping of parallel computations , 1987 .

[27]  David R. Jefferson,et al.  Virtual time , 1985, ICPP.

[28]  Demichelis,et al.  Evaluation of the , 1992, Physical review. B, Condensed matter.

[29]  P. Dickens,et al.  SRADS WITH LOCAL ROLLBACK , 1990 .

[30]  Enver Yücesan,et al.  Proceedings of the 1989 winter simulation conference , 1989 .

[31]  R. F. Brown,et al.  PERFORMANCE EVALUATION , 2019, ISO 22301:2019 and business continuity management – Understand how to plan, implement and enhance a business continuity management system (BCMS).