ABCDPlace: Accelerated Batch-Based Concurrent Detailed Placement on Multithreaded CPUs and GPUs

Abstract

Placement is an important step in modern very-large-scale integrated (VLSI) designs. Detailed placement is a placement refining procedure intensively called throughout the design flow, thus its efficiency has a vital impact on design closure. However, since most detailed placement techniques are inherently greedy and sequential, they are generally difficult to parallelize. In this article, we present a concurrent detailed placement framework, ABCDPlace, exploiting multithreading and graphic processing unit (GPU) acceleration. We propose batch-based concurrent algorithms for widely adopted sequential detailed placement techniques, such as independent set matching, global swap, and local reordering. The experimental results demonstrate that ABCDPlace can achieve $2\times $ – $5\times $ faster runtime than sequential implementations with multithreaded CPU and over $10\times $ with GPU on ISPD 2005 contest benchmarks without quality degradation. On larger industrial benchmarks, we show more than $16\times $ speedup with GPU over the state-of-the-art sequential detailed placer. ABCDPlace finishes the detailed placement of a 10-million-cell industrial design in 1 min.