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A polynomial-time custom instruction identification algorithm based on dynamic programming

机译:基于动态规划的多项式时间自定义指令识别算法

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This paper introduces an innovative algorithm for automatic instruction-set extension, which gives a pseudo-optimal solution within polynomial time to the size of a graph. The algorithm uses top-down dynamic programming strategy with the branch-and-bound algorithm in order to exploit overlapping of subproblems. Correctness of the algorithm is formally proved, and time complexity is analyzed from it. Also, it is verified that the algorithm gives an optimal solution for some type of merit functions, and has very small possibility of obtaining non-optimal solution in general. Furthermore, several experimental results are presented as evidence of the fact that the proposed algorithm has notable performance improvement.
机译:本文介绍了一种用于指令集自动扩展的创新算法,该算法在多项式时间内为图形的大小提供了伪最优解。该算法将自上而下的动态规划策略与分支定界算法结合使用,以利用子问题的重叠。正式证明了该算法的正确性,并从中分析了时间复杂度。此外,已证实该算法为某些类型的优值函数提供了最优解,并且一般而言获得非最优解的可能性很小。此外,提出了一些实验结果,以证明所提出的算法具有显着的性能改进这一事实。

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