动态软件调优的自适应算法选择方法

Proceedings of 1993 IEEE 17th International Computer Software and Applications Conference COMPSAC '93 Pub Date : 1993-11-01 DOI:10.1109/CMPSAC.1993.404185

K. Suzaki, Takio Kurita, H. Tanuma, S. Hirano

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引用次数: 2

摘要

本文提出了一种新的动态软件调优方法——自适应算法选择法(AASM)。AASM内置于库的调用序列中。当调用库时，AASM被激活。AASM根据数据和机器类型从库中注册的算法中选择并执行最优算法。因此，软件自动调优，缩短了执行时间。神经网络从注册算法的性能测试结果中学习给定机器的数据与最佳算法之间的关系。我们在以下机器上用AASM实验了一个多字符串搜索问题:CRAY X-MP/216、FACOM M 1800/30和SUN Sparc Station 2。通过这些实验，我们证明了AASM能够最大限度地减少执行时间。

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Adaptive algorithm selection method (AASM) for dynamic software tuning

This paper presents a new approach to dynamic software tuning called the adaptive algorithm selection method (AASM). The AASM is built into the calling sequence of a library. When the library is called, the AASM is activated. The AASM selects and executes the optimum algorithm from registered algorithms in a library, based on data and machine type. As a result, the software is automatically tuned and the execution time is shortened. The relation between the data and the best algorithm for a given machine is learned by a neural network from the results of performance tests of the registered algorithms. We experimented on a multi-strings search problem with the AASM on the following machines: the CRAY X-MP/216, FACOM M 1800/30, and SUN Sparc Station 2. From these experiments we demonstrated that the AASM is able to minimize the execution time.<>

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Proceedings of 1993 IEEE 17th International Computer Software and Applications Conference COMPSAC '93

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