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Estimating circuit delays in FPGAs after technology mapping

机译:在技​​术映射之后估计FpGa中的电路延迟

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摘要

An FPGA implementation requires a significant effort of the hardware designer, who optimizes FPGA designs by going through many time-consuming CAD flow iterations. These iterations provide two types of feedback: (1) the FPGA performance and (2) the identification of the parts having the highest impact on the FPGA performance. Both depend on the wirelength behavior. Studies have been dedicated to the estimation of local [5] and global [4] wirelengths, but to our knowledge both performance estimations and identification of the critical zone are not present in literature. Therefore this paper, firstly, presents a comparison of three performance estimation techniques: logic depth, Monte Carlo simulation and fast placement (ordered from low to high accuracy and runtime). Secondly, four methods identifying the critical zone are compared. Results show that Monte Carlo simulations provide a good identification of the parts having the highest impact on the performance. We conclude that Monte Carlo simulations provide useful feedback within a short runtime (about 30 times faster than placement), reducing the time-to-market of FPGA implementations.
机译:FPGA的实现需要硬件设计人员的大量努力,他需要进行许多耗时的CAD流程迭代来优化FPGA设计。这些迭代提供两种类型的反馈:(1)FPGA性能和(2)识别对FPGA性能影响最大的部件。两者都取决于线长行为。研究一直致力于估计本地[5]和全局[4]线长,但是就我们所知,性能评估和关键区域的识别在文献中都没有。因此,本文首先对三种性能估计技术进行了比较:逻辑深度,蒙特卡洛模拟和快速放置(从低到高精度和运行时间排序)。其次,比较了识别关键区域的四种方法。结果表明,蒙特卡洛模拟可以很好地识别对性能影响最大的零件。我们得出的结论是,蒙特卡洛仿真在短时间内(比布局快30倍)提供了有用的反馈,从而缩短了FPGA实现的上市时间。

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