广义匹配从理论到应用

P. Vuillod, L. Benini, G. Micheli
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引用次数: 5

摘要

我们提出了一种新的映射后优化方法。我们利用广义匹配的概念,这是一种从符号上找到库单元到布尔关系指定的多输出网络的所有可能匹配分配的技术。有几个目标:延迟约束下的面积最小化;时延约束下的功率最小化以及无约束延迟最小化。我们描述了广义匹配的理论和算法优化所需的有效和鲁棒的实现。一个基于广义匹配的工具已经实现并在MCNC'91基准套件的大型示例上进行了测试。我们在以下方面获得了相当大的改进:速度(平均6%,最高20.7%);受速度限制的面积(平均13.7%,最高29.5%);速度限制下的动力(平均22.3%,最高38.1%)。
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Generalized matching from theory to application
We present a novel approach for post-mapping optimization. We exploit the concept of generalised matching, a technique that finds symbolically all possible matching assignments of library cells to a multi-output network specified by a Boolean relation. Several objectives are targeted: area minimization under delay constraints; power minimization under delay constraints; and unconstrained delay minimization. We describe the theory of generalized matching and the algorithmic optimization required for its efficient and robust implementation. A tool based on generalized matching has been implemented and tested on large examples of the MCNC'91 benchmark suite. We obtain sizable improvements in: speed (6% in average, up to 20.7%); area under speed constraints (13.7% an average, up to 29.5%); and power under speed constraints (22.3% in average, up to 38.1%).
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