Timing local streams: Improving timeliness in data prefetching

Data prefetching technique is widely used to bridge the growing performance gap between processor and memory. Numerous prefetching techniques have been proposed to exploit data patterns and correlations in the miss address stream. In general, the miss addresses are grouped by some common characteristics, such as program counter or memory region they belong to, into localized streams to improve prefetch accuracy and coverage. However, the existing stream localization technique lacks the timing information of misses. This drawback can lead to a large fraction of untimely prefetches, which in turn limits the effectiveness of prefetching, wastes precious bandwidth and leads to high cache pollution potentially. This paper proposes a novel mechanism named stream timing technique that can largely reduce untimely prefetches and in turn increase the overall performance. Based on the proposed stream timing technique, we extend the conventional stride prefetcher and propose a new stride prefetcher called Time-Aware Stride (TAS) prefetcher. We have carried out extensive simulation experiments to verify the design of the stream timing technique and the TAS prefetcher. The simulation results show that the proposed stream timing technique is promising in reducing untimely prefetches and the IPC improvement of TAS prefetcher outperforms the existing stride prefetcher by 11%.