Measuring experimental error in microprocessor simulation

Abstract

We measure the experimental error that arises from the use of non-validated simulators in computer architecture research, with the goal of increasing the rigor of simulation-based studies. We describe the methodology that we used to validate a microprocessor simulator against a Compaq DS-10L workstation, which contains an Alpha 21264 processor. Our evaluation suite consists of a set of 21 microbenchmarks that stress different aspects of the 21264 microarchitecture. Using the microbenchmark suite as the set of workloads, we describe how we reduced our simulator error to an arithmetic mean of 2%, and include details about the specific aspects of the pipeline that required extra care to reduce the error. We show how these low-level optimizations reduce average error from 40% to less than 20% on macrobenchmarks drawn from the SPEC2000 suite. Finally, we examine the degree to which performance optimizations are stable across different simulators, showing that researchers would draw different conclusions, in some cases, if using validated simulators.