Software supports for preemptive rollback in optimistic parallel simulation on myrinet clusters

In this paper we present a communication layer for Myrinet based clusters, designed to efficiently support preemptive rollback operations in optimistic parallel simulation. Beyond standard low latency message delivery functionalities, this layer also embeds functionalities for allowing the overlying simulation application to efficiently track whether an incoming message will actually produce causality inconsistency of the currently executed simulation event upon its receipt at the application level. Exploiting these functionalities, awareness of the inconsistency precedes the message receipt at the application level, thus allowing timely event execution interruption for activating rollback procedures. Experimental results on a standard simulation benchmark show that the layer we implement allows a strong reduction of the rollback overhead which, in its turn, yields strong performance improvements (up to 33%), especially in case of large parallelism in the simulation model execution

Software Supports for Preemptive Rollback in Optimistic Parallel Simulation on Myrinet Clusters

Abstract In this paper we present a communication layer for Myrinet based clusters, designed to efficiently support preemptive rollback operations in optimistic parallel simulation. Beyond standard low latency message delivery functionalities, this layer also embeds functionalities for allowing the overlying simulation application to efficiently track whether an incoming message will actually produce causality inconsistency of the currently executed simulation event upon its receipt at the application level. Exploiting these functionalities, awareness of the inconsistency precedes the message receipt at the application level, thus allowing timely event execution interruption for activating rollback procedures. Experimental results on a standard simulation benchmark show that the layer we implement allows a strong reduction of the rollback overhead which, in its turn, yields strong performance improvements (up to 33%), especially in case of large parallelism in the simulation model execution.