Combined optimal and heuristic approaches for multiple constant multiplication

J. Thong, N. Nicolici
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引用次数: 7

Abstract

We propose new optimal and heuristic approaches for solving the multiple constant multiplication (MCM) problem. Bounded depth first search (BDFS), our proposed optimal algorithm, is benchmarked on problem sizes that are impractical for the existing optimal method. We focus on MCM problems with few constants but on large bit widths. In this scenario, we outperform the existing heuristics in minimizing the number of adders. In addition, subject to a given quality of solution, our run time is faster. We reuse our heuristics for pruning within BDFS.
多重常数乘法的组合最优与启发式方法
我们提出了新的最优和启发式方法来解决多重常数乘法(MCM)问题。我们提出的最优算法有界深度优先搜索(BDFS)是对现有最优方法不切实际的问题规模进行基准测试的。我们关注的是具有少量常数但具有较大位宽的MCM问题。在这种情况下,我们在最小化加法器数量方面优于现有的启发式算法。此外,根据给定的解决方案质量,我们的运行时间会更快。我们在BDFS中重用启发式方法进行剪枝。
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