Prefetching and Cache Management Using Task Lifetimes Vassilis

Task-based dataflow programming models and runtimes em-erge as promising candidates for programming multicore and manycore architectures. These programming models ana-lyze dynamically task dependencies at runtime and schedule independent tasks concurrently to the processing elements. In such models, cache locality, which is critical for perfor-mance, becomes more challenging in the presence of fine-grain tasks, and in architectures with many simple cores. This paper presents a combined hardware-software ap-proach to improve cache locality and offer better perfor-mance is terms of execution time and energy in the memory system. We propose the explicit bulk prefetcher (EBP) and epoch-based cache management (ECM) to help runtimes prefetch task data and guide the replacement decisions in caches. The runtime software can use this hardware sup-port to expose its internal knowledge about the tasks to the architecture and achieve more efficient task-based execution. Our combined scheme outperforms HW-only prefetchers and state-of-the-art replacement policies, improves performance by an average of 17%, generates on average 26 % fewer L2 misses, and consumes on average 28 % less energy in the components of the memory system