FPGA-Accelerated Spreading for Global Placement

Shounak Dhar, L. Singhal, M. Iyer, D. Pan
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引用次数: 1

Abstract

Placement takes a large part of the runtime in an Electronic Design Automation design implementation flow. In modern industrial and academic physical design impementation tools, global placement consumes a significant part of the overall placement runtime. Many of these global placers decouple the placement problem into two main parts - numerical optimization and spreading. In this paper, we propose a new and massively parallel spreading algorithm and also accelerate a part of this algorithm on FPGA. Our algorithm produces placements with comparable quality when integrated into a state-of-the-art academic placer. We formulate the spreading problem as a system of fluid flows across reservoirs and mathematically prove that this formulation produces flows without cycles when solved as a continuous-time system. We also propose a flow correction algorithm to make the flows monotonic, reduce total cell displacement and remove cycles which may arise during the discretization process. Our new flow correction algorithm has a better time complexity for cycle removal than previous algorithms for finding cycles in a generic graph. When compared to our previously published linear programming based spreading algorithm [1], our new fluid-flow based multi-threaded spreading algorithm is 3.44x faster, and the corresponding FPGA-accelerated version is 5.15x faster.
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fpga加速全球布局的扩展
在电子设计自动化设计实现流程中,放置占据了运行时的很大一部分。在现代工业和学术物理设计实现工具中,全局布局占用了总体布局运行时的很大一部分。许多这些全局布局解耦问题分为两个主要部分-数值优化和扩展。本文提出了一种新的大规模并行扩展算法,并在FPGA上实现了部分算法的加速。我们的算法产生的位置具有相当的质量,当整合到一个国家的最先进的学术placer。我们将扩散问题表述为储层流体流动系统,并从数学上证明了该表述作为连续时间系统求解时产生无循环流动。我们还提出了一种流动校正算法,使流动单调,减少细胞总位移,消除离散过程中可能出现的循环。本文提出的流校正算法在循环去除方面比以往的算法具有更好的时间复杂度。与我们之前发表的基于线性规划的传播算法[1]相比,我们新的基于流体流动的多线程传播算法速度提高了3.44倍,相应的fpga加速版本速度提高了5.15倍。
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