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The Method of Parallel Optimization and Parallel Recognition Based on Data Dependence

机译:基于数据依赖性的并行优化和并行识别方法

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摘要

For application programs in scientific and technological fields have grown increasingly large and complex, it is becoming more difficult to parallelize these programs by hand using message-passing libraries. To reduce this difficulty, we are researching the compilation technology for serial program automatic parallelization. In this paper, the author puts forward a kind of parallel recognition algorithm in parallelization compiler. In the algorithm the author adopts the idea of the medium grain parallel. Through this algorithm, the parallelization compiler can identify all of the parallelizable blocks. So that the application programs can be speeded up and the execution ability can be improved when the blocks execute on multi-processors. Parallel processing often can make the runtime of application programs shorter than serial processing, but if the radio of parallel workload to overhead about creating parallel thread or the radio of parallel workload to parallel thread number is small, parallel execution can degrades program performance. To solve this problem, the author proposes several parallel optimization approaches in the end of the paper.
机译:对于科技领域的应用程序已经增长越来越大而复杂,越来越难以使用消息传递的库并行化这些程序。为了减少这种困难,我们正在研究串行程序自动并行化的编译技术。在本文中,作者在并行化编译器中提出了一种并行识别算法。在该算法中,作者采用介质谷物的思想并行。通过该算法,并行化编译器可以识别所有并行块。因此,当在多处理器上执行块时,可以加速应用程序可以加速,并且可以提高执行能力。并行处理通常可以使应用程序的运行时间短于串行处理,但是,如果并行工作负载的无线电对创建并行工作负载的开销或并行工作负载到并行线号小,则并行执行可能会降低程序性能。为了解决这个问题,提议在纸质末尾提出了几种并行优化方法。

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