Affiliation:
1. Carnegie Mellon University
Abstract
Coherent read misses in shared-memory multiprocessors account for a substantial fraction of execution time in many important scientific and commercial workloads. We propose Temporal Streaming, to eliminate coherent read misses by streaming data to a processor in advance of the corresponding memory accesses. Temporal streaming dynamically identifies address sequences to be streamed by exploiting two common phenomena in shared-memory access patterns: (1) temporal address correlation - groups of shared addresses tend to be accessed together and in the same order, and (2) temporal stream locality - recently-accessed address streams are likely to recur. We present a practical design for temporal streaming. We evaluate our design using a combination of trace-driven and cycle-accurate full-system simulation of a cache-coherent distributed shared-memory system. We show that temporal streaming can eliminate 98% of coherent read misses in scientific applications, and between 43% and 60% in database and web server workloads. Our design yields speedups of 1.07 to 3.29 in scientific applications, and 1.06 to 1.21 in commercial workloads.
Publisher
Association for Computing Machinery (ACM)
Cited by
8 articles.
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2. Pythia: A Customizable Hardware Prefetching Framework Using Online Reinforcement Learning;MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture;2021-10-17
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