Work

CSF: Fixed-Outline Floorplanning Based on the Conjugate Subgradient Algorithm and Assisted by Q-Learning

Year: 2025

Type: article

Abstract: Analytical floorplanning algorithms are prone to local convergence and struggle to generate high-quality results; therefore, this paper proposes a nonsmooth analytical placement model and develops a Q-learning-assisted conjugate subgradient algorithm (CSAQ) for efficient floorplanning that addresses these issues. By integrating a population-based strategy and an adaptive step size adjustment driven by Q-learning, the CSAQ strikes a balance between exploration and exploitation to avoid suboptimal solutions in fixed-outline floorplanning scenarios. Experimental results on the MCNC and GSRC benchmarks demonstrate that the proposed CSAQ not only effectively solves global placement planning problems but also significantly outperforms existing constraint graph-based legalization methods, as well as the improved variants, in terms of the efficiency of generating legal floorplans. For hard module-only placement scenarios, it exhibits competitive performance compared to the state-of-the-art algorithms.

Source: Electronics

DOI: 10.3390/electronics14244893

Authors: Xinyan Meng, Huabin Cheng, Yu Chen, Jianguo Hu, Ning Xu

Institutions: Wuhan University of Technology, Wuchang Shouyi University, Sun Yat-sen University

Language: English

Topic: VLSI and FPGA Design Techniques

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

Funder: Science and Technology Planning Project of Guangdong Province