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Design space exploration of RTL datapaths using Rent parameter based stochastic wirelength estimation

机译:基于Rent参数的随机线长估计对RTL数据路径的设计空间探索

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We present an assessment of a priori stochastic wire-length estimation as a viable technique for evaluating the interconnect requirements of designs explored in RTL datapath synthesis. The model estimates the wirelength requirements of a gate level netlist a priori, based on Rentian parameters extracted dynamically from RTL netlists. Experimental results indicate that the wirelength estimates of our dynamic Rent parameter extraction method are in agreement within an average of 3.96% to those obtained from designs synthesized by a commercial place-and-route tool, while offering an average speedup of 278% over physical synthesis, suggesting that stochastic wirelength estimation methods are a viable approach to guide design space exploration in high-level synthesis
机译:我们提出对先验随机线长估计的评估,作为评估RTL数据路径综合中探索的设计的互连要求的可行技术。该模型根据从RTL网表动态提取的Rentian参数,先验估计门级网表的线长要求。实验结果表明,我们的动态Rent参数提取方法的线长估计与通过商业布局布线工具合成的设计所获得的平均线长估计相差3.96%,而与物理合成相比,平均线速估计可提高278% ,表明随机线长估计方法是指导高级综合中设计空间探索的可行方法

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