Intrinsic data locality of modern scientific workloads

Abstract

Understanding the intrinsic data locality of a workload is essential to understanding and predicting cache performance. The intrinsic data locality of a particular application or workload can be measured in a microarchitecture-independent manner. The data resulting from these measurements ideally can be used to develop an analytic model for predicting memory performance on different cache sizes and configurations. Many studies on data locality use cache hit ratios, a microarchitecture-dependent metric, to examine locality. In this paper, we present a microarchitecture-dependent and a microarchitecture-independent characterization of the SPEC2000 workloads. We present quantitative statistics on the different types of data locality (e.g. spatial and temporal) exhibited by these workloads and we show that the composite intrinsic locality can be correlated to locality measured by cache hit ratio.