首页> 外文期刊>IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems >FlowMap: an optimal technology mapping algorithm for delay optimization in lookup-table based FPGA designs
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FlowMap: an optimal technology mapping algorithm for delay optimization in lookup-table based FPGA designs

机译:FlowMap:基于查找表的FPGA设计中用于延迟优化的最佳技术映射算法

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The field programmable gate-array (FPGA) has become an important technology in VLSI ASIC designs. In the past few years, a number of heuristic algorithms have been proposed for technology mapping in lookup-table (LUT) based FPGA designs, but none of them guarantees optimal solutions for general Boolean networks and little is known about how far their solutions are away from the optimal ones. This paper presents a theoretical breakthrough which shows that the LUT-based FPGA technology mapping problem for depth minimization can be solved optimally in polynomial time. A key step in our algorithm is to compute a minimum height K-feasible cut in a network, which is solved optimally in polynomial time based on network flow computation. Our algorithm also effectively minimizes the number of LUT's by maximizing the volume of each cut and by several post-processing operations. Based on these results, we have implemented an LUT-based FPGA mapping package called FlowMap. We have tested FlowMap on a large set of benchmark examples and compared it with other LUT-based FPGA mapping algorithms for delay optimization, including Chortle-d, MIS-pga-delay, and DAG-Map. FlowMap reduces the LUT network depth by up to 7% and reduces the number of LUT's by up to 50% compared to the three previous methods.
机译:现场可编程门阵列(FPGA)已成为VLSI ASIC设计中的一项重要技术。在过去的几年中,已经提出了许多启发式算法,用于基于查找表(LUT)的FPGA设计中的技术映射,但是它们都不能保证通用布尔网络的最佳解决方案,而对于它们的解决方案还有多远的了解却很少从最佳的。本文提出了一项理论突破,表明可以在多项式时间内最佳解决基于LUT的FPGA技术的深度最小化映射问题。我们算法的关键步骤是计算网络中的最小高度K可行割,这是根据网络流量计算在多项式时间内最佳解决的。我们的算法还通过最大程度地增加每个切割的数量并通过若干后处理操作,有效地最小化了LUT的数量。基于这些结果,我们实现了一个名为FlowMap的基于LUT的FPGA映射包。我们已经在大量基准示例上测试了FlowMap,并将其与其他基于LUT的FPGA映射算法进行延迟优化进行了比较,包括Chortle-d,MIS-pga-delay和DAG-Map。与之前的三种方法相比,FlowMap最多可将LUT网络深度减少7%,并将LUT的数量减少多达50%。

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