Performance Analysis of Asynchronous Circuits and Systems using Stochastic Timed Petri Nets

. This paper describes and extends a recently developed approach for performance analysis of asynchronous circuits modeled with stochastic timed Petri nets (STPNs) with unique- and free-choice places and arbitrary delay distributions. The approach analyzes finite STPN executions to derive closed-form expressions for lower and upper bounds on the performance estimates that can be efficiently evaluated using standard statistical methods. The mean of the derived upper and lower bounds thus provides an estimate of the performance metric which has a well-defined error interval. Moreover, we can often make the error interval arbitrarily small by analyzing longer STPN executions at the cost of additional run-time. Experiments on several asynchronous systems demonstrate the high quality of our estimates and the efficiency of the technique. The experiments include the performance analysis of a fullscale Petri net model of Intel's asynchronous instruction length decoding and steering unit RAPPID..