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Flow-sensitive runtime estimation: an enhanced hot spot detection heuristics for embedded java just-in-time compilers

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SOFTWARE-PRACTICE & EXPERIENCE 2016年第6期46卷 841-864页

作者： Lee, Seong-Won Moon, Soo-Mook Kim, Seong-Moo Seoul Natl Univ Sch Elect Engn & Comp Sci Seoul South Korea

java just-in-time compilers often compile only hot methods because the compilation overhead is a part of the running time. This requires precise and efficient hot spot detection, which includes distinguishing hot methods from cold ones, detecting them as early as possible, and paying a small detection overhead. Hot spot detection is especially important in embedded applications because they show more of a start-up phase behavior of a regular application where methods are not executed heavily, so the hot methods are not definite. Because a long-running method is likely to be a hot method, we can detect a hot method by measuring its running time during interpretation. However, precise measurement of the running time during execution is too expensive, especially in embedded systems, so many counter-based heuristics have been proposed to estimate it such as Oracle's HotSpot heuristic. One problem is that although the overhead of these heuristics is low, they do not estimate the running time precisely, which may lead to imprecise hot spot *** paper proposes a new hot spot detection heuristic called flow-sensitive runtime estimation, which can estimate the running time more precisely than others with a relatively low overhead. It only counts important bytecode instructions dynamically, but it can obtain the precise count of all interpreted bytecode instructions with a simple arithmetic calculation. We also propose a static analysis technique to predict those hot methods which spends a huge execution time once invoked, so as to compile them at their first invocation. Our experimental results show that these techniques can improve the performance by as much as an average of 7.4% compared with the HotSpot heuristic for the benchmarks when they run once, which is often regarded as showing the start-up phase behavior. Even for real embedded java applications such as the digital TV java Xlet applications, our techniques can improve the user response time by an averag

关键词： java just-in-time compilation hot spot detection start-up behavior HotSpot heuristic DTV Xlet application

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Enhanced hot spot detection heuristics for embedded java just-in-time compilers 08

Enhanced hot spot detection heuristics for embedded java jus...

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Conference on Languages, Compilers and Tools for Embedded Systems

作者： Lee, Seong-Won Moon, Soo-Mook Kim, Seong-Moo Seoul Natl Univ Sch Elect Engn Seoul 151 South Korea

ISBN: (纸本)9781605581040

Most java just-in-time compilers (JITC) try to compile only hot methods since the compilation overhead is part of the running time. This requires precise and efficient hot spot detection, which includes distinguishing hot methods from cold methods, detecting them as early as possible, and paying a small runtime overhead for detection. A hot method could be identified by measuring its running time during interpretation since a long-running method is likely to be a hot method. However, precise measurement of the running time during execution is too expensive, especially in embedded systems, so many counter-based heuristics have been proposed to estimate it. The Simple heuristic counts only method invocations without any consideration of loops [1], while Sun's HotSpot heuristic counts loop iterations as well, but does not consider loop sizes or method sizes [2,14]. The static analysis heuristic estimates the running time of a method by statically analyzing loops or heavy-cost bytecodes but does not measure their dynamic counts [3]. Although the overhead of these heuristics is low, they do not estimate the running time precisely, which may lead to imprecise hot spot detection. This paper proposes a new hot spot detection heuristic which can estimate the running time more precisely than others with a relatively low overhead. It dynamically counts only important bytecodes interpreted, but with a simple arithmetic calculation it can obtain the precise count of all interpreted bytecodes. We also propose employing a static analysis technique to predict those hot methods which spend a huge execution time once invoked. This static prediction can allow compiling these methods at their first-invocation, complementing the proposed dynamic estimation technique. We implemented both, which led to a performance benefit of 10% compared to the HotSpot heuristic.

关键词： performance experimentation languages java just-in-time compilation hot spot detection Sun's HotSpot heuristic java virtual machine J2ME CDC

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Enhanced hot spot detection heuristics for embedded java just-in-time compilers

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ACM SIGPLAN NOTICES 2008年第7期43卷 13-22页

作者： Lee, Seong-Won Moon, Soo-Mook Kim, Seong-Moo Seoul Natl Univ Sch Elect Engn Seoul 151 South Korea

关键词： performance experimentation languages java just-in-time compilation hot spot detection Sun's HotSpot heuristic java virtual machine J2ME CDC

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