矢量搜索器:寻找矢量势的工具

WPMVP '14 Pub Date : 2014-02-16 DOI:10.1145/2568058.2568069
G. C. Evans, S. Abraham, B. Kuhn, D. Padua
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引用次数: 11

摘要

矢量指令在现代计算机中的重要性与日俱增。几乎所有的体系结构都包含某种形式的矢量指令,并且随着设计的更新,指令的大小也有增长的趋势。为了利用这些系统提供的性能,程序必须使用这些指令,但它们并不总是这样做。利用这些扩展的工具需要程序员的帮助,要么手工编码,要么向编译器提供提示。我们介绍Vector Seeker,一个帮助研究现有代码中向量并行性的工具。Vector Seeker与程序的执行一起运行,以乐观地测量存在的向量并行性。除了描述Vector Seeker之外,本文还使用Petascale应用协作团队(PACT)的两个应用程序和Media Bench II的八个应用程序来评估其有效性。将这些结果与人工矢量化研究的已知结果进行比较。最后,我们使用该工具对Numerical Recipes和TSVC中的代码进行自动分析,并将结果与Intel的ICC自动矢量化算法进行比较。
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Vector seeker: a tool for finding vector potential
The importance of vector instructions is growing in modern computers. Almost all architectures include some form of vector instructions and the tendency is for the size of the instructions to grow with newer designs. To take advantage of the performance that these systems offer, it is imperative that programs use these instructions, and yet they do not always do so. The tools to take advantage of these extensions require programmer assistance either by hand coding or providing hints to the compiler. We present Vector Seeker, a tool to help investigate vector parallelism in existing codes. Vector Seeker runs with the execution of a program to optimistically measure the vector parallelism that is present. Besides describing Vector Seeker, the paper also evaluates its effectiveness using two applications from Petascale Application Collaboration Teams (PACT) and eight applications from Media Bench II. These results are compared to known results from manual vectorization studies. Finally, we use the tool to automatically analyze codes from Numerical Recipes and TSVC and then compare the results with the automatic vectorization algorithms of Intel's ICC.
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