Perspective: A Sensible Approach to Speculative Automatic Parallelization
Sotiris Apostolakis, Ziyang Xu, Greg Chan, Simone Campanoni, David I. August
摘要
The promise of automatic parallelization, freeing programmers from the error-prone and time-consuming process of making efficient use of parallel processing resources, remains unrealized. For decades, the imprecision of memory analysis limited the applicability of non-speculative automatic parallelization. The introduction of speculative automatic parallelization overcame these applicability limitations, but, even in the case of no misspeculation, these speculative techniques exhibit high communication and bookkeeping costs for validation and commit. This paper presents Perspective, a speculative-DOALL parallelization framework that maintains the applicability of speculative techniques while approaching the efficiency of non-speculative ones. Unlike current approaches which subsequently apply speculative techniques to overcome the imprecision of memory analysis, Perspective combines a novel speculation-aware memory analyzer, new efficient speculative privatization methods, and a planning phase to select a minimal-cost set of parallelizationenabling transforms. By reducing speculative parallelization overheads in ways not possible with prior parallelization systems, Perspective obtains higher overall program speedup (23.0× for 12 general-purpose C/C++ programs running on a 28-core shared-memory commodity machine) than Privateer (11.5×), the prior automatic DOALL parallelization system with the highest applicability. CCS Concepts • Software and its engineering → Compilers; Multithreading.
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引用它的顶会 Paper12
- T4: Compiling Sequential Code for Effective Speculative Parallelization in HardwareVictor A. Ying, Mark C. Jeffrey, Daniel SánchezISCA 2020 · 被引用 25 次
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- Scalable FSM parallelization via path fusion and higher-order speculationJunqiao Qiu, Xiaofan Sun, Amir Hossein Nodehi Sabet, Zhijia ZhaoASPLOS 2021 · 被引用 16 次
- Practically Correct, Just-in-Time Shell Script ParallelizationKonstantinos Kallas, Tammam Mustafa, Jan Bielak, Dimitris Karnikis 等OSDI 2022 · 被引用 13 次
- SCAF: a speculation-aware collaborative dependence analysis frameworkSotiris Apostolakis, Ziyang Xu, Zujun Tan, Greg Chan 等PLDI 2020 · 被引用 12 次
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