Capacity metric for Chip Heterogeneous Multiprocessors

Chip Heterogeneous Multiprocessors (CHMs) are increasingly used to execute multichannel, heterogeneous workloads, often in the service of single users. Multichannel inputs can be processed at different rates and in a variety of combinations. We show that performance evaluation of the CHMs that process multichannel workloads requires a new performance metric, capacity, which we introduce in this paper. We show how capacity is a successor to throughput, through an automobile production analogy. We include experimental results to illustrate the form and usefulness of the new metric as well as contrast it with Pareto optimization.