Adaptive memory management and optimism control in time warp

Abstract

It is widely believed that the Time Warp protocol for parallel discrete event simulation is prone to two potential problems: an excessive amount of wasted, rolled back computation resulting from “rollback thrashing” behaviors, and inefficient use of memory, leading to poor performance of virtual memory and/or multiprocessor cache systems. An adaptive mechanism is proposed based on the Cancelback memory management protocol for shared-memory multiprocessors that dynamically controls the amount of memory used in the simulation in order to maximize performance. The proposed mechanism is adaptive in the sense that it monitors the execution of the Time Warp program, and using simple models, automatically adjusts the amount of memory used to reduce Time Warp overheads (fossil collection, Cancelback, the amount of rolled back computation, etc.) to a manageable level. We describe an implementation of this mechanism on a shared memory, Kendall Square Research KSR-1, multiprocessor and demonstrate its effectiveness in automatically maximizing performance while minimizing memory utilzation, for several synthetic and benchmark discrete event simulation applications. We also demonstrate the adaptive ability of the mechanism by showing that it “tracks” the time-varying nature of a communication network simulation.