A Simulated Annealing Technique for Optimizing Time Warp Simulation

According to Moore's law the complexity of VLSI circuits has doubled approximately every two years, resulting in simulation becoming the major bottleneck in the circuit design process. Parallel and distributed simulations can be applied as fast, cost effective approaches to the simulation of large, complex circuits. In this paper, a simple yet effective simulated annealing-based approach is proposed to optimize the choice of a time window for optimistic parallel simulation. We chose gate level circuits simulations as our experimental vehicle. Our results show up to a 52% improvement in the simulation time using our simulated annealing algorithm. To the best of our knowledge, this is the first time that SA has been applied to optimize the performance of Time Warp simulations.

[1]  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.

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

[3]  Carl Tropper,et al.  XTW, a parallel and distributed logic simulator , 2005, Workshop on Principles of Advanced and Distributed Simulation (PADS'05).

[4]  Wei Zhang,et al.  On the Scalability of Parallel Verilog Simulation , 2009, 2009 International Conference on Parallel Processing.

[5]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[6]  Jun Wang,et al.  Optimizing time warp simulation with reinforcement learning techniques , 2007, 2007 Winter Simulation Conference.

[7]  Carl Tropper,et al.  DVS: an object-oriented framework for distributed Verilog simulation , 2003, Seventeenth Workshop on Parallel and Distributed Simulation, 2003. (PADS 2003). Proceedings..

[8]  Alan Weiss,et al.  An analysis of rollback-based simulation , 1991, TOMC.

[9]  Richard M. Fujimoto,et al.  Adaptive Flow Control in Time Warp , 1997, Workshop on Parallel and Distributed Simulation.

[11]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[12]  Yury Nikulin Simulated annealing algorithm for the robust spanning tree problem , 2008, J. Heuristics.

[13]  Carl Tropper,et al.  Scalable Clustered Time Warp and Logic Simulation , 1999, VLSI Design.

[14]  R.M. Fujimoto,et al.  Parallel and distributed simulation systems , 2001, Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304).

[15]  Pedro M. Vilarinho,et al.  A simulated annealing approach for manufacturing cell formation with multiple identical machines , 2003, Eur. J. Oper. Res..

[16]  Ben Cohen VHDL Coding Styles and Methodologies , 1995 .

[17]  Santosh S. Vempala,et al.  Simulated Annealing for Convex Optimization , 2004 .

[18]  K. Mani Chandy,et al.  Asynchronous distributed simulation via a sequence of parallel computations , 1981, CACM.