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

Placement is an important step in modern verylarge-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 2x -5x faster runtime than sequential implementations with multithreaded CPU and over 10x with GPU on ISPD 2005 contest benchmarks without quality degradation. On larger industrial benchmarks, we show more than 16x 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.