Toward efficient and robust software speculative parallelization on multiprocessors

Author:

Cintra Marcelo1,Llanos Diego R.2

Affiliation:

1. University of Edinburgh, Edinburgh, UK

2. Universidad de Valladolid, Valladolid, Spain

Abstract

With speculative parallelization, code sections that cannot be fully analyzed by the compiler are aggressively executed in parallel. Hardware schemes are fast but expensive and require modifications to the processors and memory system. Software schemes require no extra hardware but can be inefficient.This paper proposes a new software-only speculative parallelization scheme. The scheme is developed after a systematic evaluation of the design options available and is shown to be efficient and robust and to outperform previously proposed schemes. The novelty and performance advantage of the scheme stem from the use of carefully tuned data structures, synchronization policies, and scheduling mechanisms. Experimental results show that our scheme has small overheads and, for applications with few or no data dependence violations, realizes on average 71% of the speedup of a manually parallelized version of the code, outperforming two recently proposed software-only speculative parallelization schemes. For applications with many data dependence violations, our performance monitors and switches can effectively curb the performance degradation.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 26 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. Recurrence Analysis for Automatic Parallelization of Subscripted Subscripts;Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming;2024-02-20

2. Performance Comparison of Speculative Taskloop and OpenMP-for-Loop Thread-Level Speculation on Hardware Transactional Memory;2022 21st International Symposium on Parallel and Distributed Computing (ISPDC);2022-07

3. On the choice of the best chunk size for the speculative execution of loops;PLOS ONE;2022-05-17

4. Using Hardware Transactional Memory to Implement Speculative Privatization in OpenMP;Languages and Compilers for Parallel Computing;2022

5. Binary-level data dependence analysis of hot execution regions using abstract interpretation at runtime;PLOS ONE;2020-04-09

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