Task Scheduling on Manycore Processors with Home Caches

Abstract

AbstractModern manycore processors feature a highly scalable and software-configurable cache hierarchy. For performance, manycore programmers will not only have to efficiently utilize the large number of cores but also understand and configure the cache hierarchy to suit the application. Relief from this manycore programming nightmare can be provided by task-based programming models where programmers parallelize using tasks and an architecture-specific runtime system maps tasks to cores and in addition configures the cache hierarchy. In this paper, we focus on the cache hierarchy of the Tilera TILEPro64 processor which features a software-configurable coherence waypoint called the home cache. We first show the runtime system performance bottleneck of scheduling tasks oblivious to the nature of home caches. We then demonstrate a technique in which the runtime system controls the assignment of home caches to memory blocks and schedules tasks to minimize home cache access penalties. Test results of our technique have shown a significant execution time performance improvement on selected benchmarks leading to the conclusion that by taking processor architecture features into account, task-based programming models can indeed provide continued performance and allow programmers to smoothly transit from the multicore to manycore era.KeywordsTask ScheduleData CacheAccess LatencyRuntime SystemStudy BenchmarkThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.