A cost-driven compilation framework for speculative parallelization of sequential programs

Author:

Du Zhao-Hui1,Lim Chu-Cheow2,Li Xiao-Feng1,Yang Chen1,Zhao Qingyu1,Ngai Tin-Fook2

Affiliation:

1. Intel China Ltd., Beijing, China

2. Intel Corporation, Santa Clara, CA

Abstract

The emerging hardware support for thread-level speculation opens new opportunities to parallelize sequential programs beyond the traditional limits. By speculating that many data dependences are unlikely during runtime, consecutive iterations of a sequential loop can be executed speculatively in parallel. Runtime parallelism is obtained when the speculation is correct. To take full advantage of this new execution model, a program needs to be programmed or compiled in such a way that it exhibits high degree of speculative thread-level parallelism. We propose a comprehensive cost-driven compilation framework to perform speculative parallelization. Based on a misspeculation cost model, the compiler aggressively transforms loops into optimal speculative parallel loops and selects only those loops whose speculative parallel execution is likely to improve program performance. The framework also supports and uses enabling techniques such as loop unrolling, software value prediction and dependence profiling to expose more speculative parallelism. The proposed framework was implemented on the ORC compiler. Our evaluation showed that the cost-driven speculative parallelization was effective. Our compiler was able to generate good speculative parallel loops in ten Spec2000Int benchmarks, which currently achieve an average 8% speedup. We anticipate an average 15.6% speedup when all enabling techniques are in place.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 29 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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3