학술논문
An Adaptive Sequential Decision Making Flow for FPGAs using Machine Learning
Document Type
Conference
Author
Source
2022 International Conference on Microelectronics (ICM) Microelectronics (ICM), 2022 International Conference on. :34-37 Dec, 2022
Subject
Language
Abstract
In this paper we propose a smart and novel machine learning framework that is capable of automatically selecting the most effective wirelength model within GPlace3.0 FPGA placement flow. Results obtained indicate that the machine learning framework is capable of selecting the correct flow with a high accuracy. The proposed method is general enough to be used within any FPGA/ASIC CAD flow.