一种新的用于开发硬件辅助指令的习语识别框架

ASPLOS XII Pub Date : 2006-10-23 DOI:10.1145/1168857.1168905
M. Kawahito, H. Komatsu, T. Moriyama, H. Inoue, T. Nakatani
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引用次数: 7

摘要

现代处理器支持硬件辅助指令(如IBM zSeries上的TRT和TROT指令)来加速某些功能,如分隔符搜索和字符转换。这种特殊指令经常用于高性能库,但除了一些有限的情况外,它们还没有很好地用于优化编译器。我们提出了一种新的成语识别技术,该技术源自拓扑嵌入算法[4],可以比以前的方法更积极地检测输入程序中的成语模式。即使代码段与习惯用法不完全匹配,我们的方法也可以检测到模式。例如,我们可以检测习语模式中包含附加代码的代码段。我们基于Java即时(JIT)编译器(它是J9 Java虚拟机的一部分)实现了新的习语识别方法,并且在IBM zSeries和IBM pSeries的某些型号上,我们为特殊硬件辅助指令支持了几个重要的习语。为了证明我们技术的有效性,我们做了两个实验。第一个是看看与之前的方法相比,我们能检测到多少模式。第二个是看看我们能在之前的方法上实现多少性能改进。对于第一个实验,我们使用Java Compatibility Kit (JCK) API测试。对于第二个示例,我们使用IBM XML解析器、SPECjvm98和SPCjbb2000。总之,与使用精确模式匹配的基线实现相比,我们的算法在JCK测试中转换的循环多了75%。我们还观察到,在z990上,XML解析器的性能平均提高了64%,SPECjvm98提高了1%,SPECjbb2000提高了2%。最后,我们观察到JIT编译时间只增加了0.32%到0.44%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new idiom recognition framework for exploiting hardware-assist instructions
Modern processors support hardware-assist instructions (such as TRT and TROT instructions on IBM zSeries) to accelerate certain functions such as delimiter search and character conversion. Such special instructions have often been used in high performance libraries, but they have not been exploited well in optimizing compilers except for some limited cases. We propose a new idiom recognition technique derived from a topological embedding algorithm [4] to detect idiom patterns in the input program more aggressively than in previous approaches. Our approach can detect a pattern even if the code segment does not exactly match the idiom. For example, we can detect a code segment that includes additional code within the idiom pattern. We implemented our new idiom recognition approach based on the Java Just-In-Time (JIT) compiler that is part of the J9 Java Virtual Machine, and we supported several important idioms for special hardware-assist instructions on the IBM zSeries and on some models of the IBM pSeries. To demonstrate the effectiveness of our technique, we performed two experiments. The first one is to see how many more patterns we can detect compared to the previous approach. The second one is to see how much performance improvement we can achieve over the previous approach. For the first experiment, we used the Java Compatibility Kit (JCK) API tests. For the second one we used IBM XML parser, SPECjvm98, and SPCjbb2000. In summary, relative to a baseline implementation using exact pattern matching, our algorithm converted 75% more loops in JCK tests. We also observed significant performance improvement of the XML parser by 64%, of SPECjvm98 by 1%, and of SPECjbb2000 by 2% on average on a z990. Finally, we observed the JIT compilation time increases by only 0.32% to 0.44%.
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