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A Technique for the Effective and Automatic Reuse of Classical Compiler Optimizations on Multithreaded Code

机译:多线程代码上的经典编译优化的有效和自动重用技术

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A large body of data-flow analyses exists for analyzing and optimizing sequential code. Unfortunately, much of it cannot be directly applied on parallel code, for reasons of correctness. This paper presents a technique to automatically, aggressively, yet safely apply sequentially-sound data-flow transformations, without change, on shared-memory programs. The technique is founded on the notion of program references being "siloed" on certain control-flow paths. Intuitively, siloed references are free of interference from other threads within the confines of such paths. Data-flow transformations can, in general, be unblocked on siloed references. The solution has been implemented in a widely used compiler. Results on benchmarks from SPLASH-2 show that performance improvements of up to 41 % are possible, with an average improvement of 6% across all the tested programs over all thread counts.
机译:存在大量的数据流分析,用于分析和优化顺序代码。不幸的是,由于正确性的原因,它的大部分都无法直接应用于并行代码。本文介绍了一种自动,积极,且安全地应用序列声音数据流变换的技术,而不会在共享内存程序上进行更改。该技术建立在某些控制流路径上“淤泥”的程序引用的概念。直观地,静默的参考文献没有来自这种路径的范围内的其他线程的干扰。一般而言,数据流变换可以在静默引用上解除阻塞。解决方案已在广泛使用的编译器中实现。结果来自Splash-2的基准,表明,最高可达41%的性能提高是可能的,平均改善在所有螺纹计数上的所有测试程序中的6%。

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