Selective, accurate, and timely self-invalidation using last-touch prediction

Author:

Lai An-Chow1,Falsafi Babak1

Affiliation:

1. School of Electrical & Computer Engineering, Purdue University, 1285 EE Building, West Lafayette, IN

Abstract

Communication in cache-coherent distributed shared memory (DSM) often requires invalidating (or writing back) cached copies of a memory block, incurring high overheads. This paper proposes Last-Touch Predictors (LTPs) that learn and predict the “last touch” to a memory block by one processor before the block is accessed and subsequently invalidated by another. By predicting a last-touch and (self-)invalidating the block in advance, an LTP hides the invalidation time, significantly reducing the coherence overhead. The key behind accurate last-touch prediction is trace-based correlation, associating a last-touch with the sequence of instructions (i.e., a trace) touching the block from a coherence miss until the block is invalidated. Correlating instructions enables an LTP to identify a last-touch to a memory block uniquely throughout an application's execution. In this paper, we use results from running shared-memory applications on a simulated DSM to evaluate LTPs. The results indicate that: (1) our base case LTP design, maintaining trace signatures on a per-block basis, substantially improves prediction accuracy over previous self-invalidation schemes to an average of 79%; (2) our alternative LTP design, maintaining a global trace signature table, reduces storage overhead but only achieves an average accuracy of 58%; (3) last-touch prediction based on a single instruction only achieves an average accuracy of 41% due to instruction reuse within and across computation; and (4) LTP enables selective, accurate, and timely self-invalidation in DSM, speeding up program execution on average by 11%.

Publisher

Association for Computing Machinery (ACM)

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Applying machine learning to enhance the cache performance using reuse distance;Evolutionary Intelligence;2022-05-27

2. Speculation Meets Checkpointing;Computational Science – ICCS 2006;2006

3. Using Speculative Push for Unnecessary Checkpoint Creation Avoidance;Distributed Applications and Interoperable Systems;2006

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