Parallel efficient implementation of hierarchical algorithms for module placement of large chips

L. Yang
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Abstract

The PROUD module placement algorithm mainly uses a hierarchical decomposition technique and the solution of sparse linear systems based on a resistive network analogy. It has been shown that the PROUD algorithm can achieve a comparable design of the placement problems for very large circuits with the best placement algorithm based on simulated annealing, but with several order of magnitude faster. The modified PROUD, namely MPROUD algorithm by perturbing the coefficient matrices performs much faster that the original PROUD algorithm. Due to the instability and unguaranteed convergence of MPROUD algorithm we have proposed a new convergent and numerically stable PROUD, namely Improved PROUD algorithm, denoted as IPROUD with attractive computational costs to solve the module placement problems by making use of the MINRES method based on Lanczos process. In this paper, we subsequently propose parallel versions of the original, modified and improved PROUD algorithms that combine both fine and coarse grain parallelism to obtain another order of magnitude improvement in the runtime without loss of the quality of the layout. Experimental results using Message Passing Interface (MPI) on various multiprocessor systems are reported showing its advantages for a variety of large layout benchmark circuits.
大芯片模块放置分层算法的并行高效实现
PROUD模块放置算法主要采用层次分解技术和基于电阻网络类比的稀疏线性系统求解。研究表明,该算法可以与基于模拟退火的最佳布局算法实现相当的超大电路布局问题设计,但速度要快几个数量级。改进的PROUD算法,即通过扰动系数矩阵的MPROUD算法,比原PROUD算法执行速度快得多。针对MPROUD算法的不稳定性和不保证收敛性的问题,我们提出了一种新的收敛且数值稳定的PROUD算法,即改进的PROUD算法,记为IPROUD,计算成本较低,利用基于Lanczos过程的MINRES方法解决模块放置问题。在本文中,我们随后提出了原始、修改和改进的PROUD算法的并行版本,这些算法结合了细粒度和粗粒度并行性,在不损失布局质量的情况下,在运行时获得了另一个数量级的改进。在各种多处理器系统上使用消息传递接口(Message Passing Interface, MPI)的实验结果显示了它在各种大布局基准电路中的优势。
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