Evaluating the Performance of Cache-Affinity Scheduling in Shared-Memory Multiprocessors

As a process executes on a CPU, it builds up state in that CPU's cache. In multiprogrammed workloads, the opportunity to reuse this state may be lost when a process gets rescheduled, either because intervening processes destroy its cache state or because the process may migrate to another processor. In this paper, we explore affinity scheduling, a technique that helps reduce cache misses by preferentially scheduling a process on a CPU where it has run recently. Our study focuses on a bus-based multiprocessor executing a variety of workloads, including mixes of scientific, software development, and database applications. In addition to quantifying the performance benefits of exploiting affinity, our study is distinctive in that it provides low-level data from a hardware performance monitor that details why the workloads perform as they do. Overall, for the workloads studied, we show that affinity scheduling reduces the number of cache misses by 7--36%, resulting in execution time improv..