MDP-trees: Multi-domain macro placement for ultra large-scale mixed-size designs

Yen Chun Liu, Tung Chieh Chen, Yao Wen Chang, Sy Yen Kuo

研究成果: 圖書/報告稿件的類型會議稿件同行評審

5 引文 斯高帕斯(Scopus)

摘要

In this paper, we present a new hybrid representation of slicing trees and multi-packing trees, called multi-domain-packing trees (MDP-trees), for macro placement to handle ultra large-scale multi-domain mixed-size designs. A multi-domain design typically consists of a set of mixed-size domains, each with hundreds/thousands of large macros and (tens of) millions of standard cells, which is often seen in modern high-end applications (e.g., 4G LTE products and upcoming 5G ones). To the best of our knowledge, there is still no published work specifically tackling the domain planning and macro placement simultaneously. Based on binary trees, the MDP-tree is very efficient and effective for handling macro placement with multiple domains. Previous works on macro placement can handle only single-domain designs, which do not consider the global interactions among domains. In contrast, our MDP-trees plan domain regions globally, and optimize the interconnections among domains and macro/cell positions simultaneously. The placement area of each domain is well reserved, and the macro displacement is minimized from initial macro positions of the design prototype. Experimental results show that our approach can significantly reduce both the average half-perimeter wirelength and the average global routing wirelength.

原文英語
主出版物標題ASP-DAC 2019 - 24th Asia and South Pacific Design Automation Conference
發行者Institute of Electrical and Electronics Engineers Inc.
頁面317-322
頁數6
ISBN(電子)9781450360074
DOIs
出版狀態已出版 - 21 01 2019
對外發佈
事件24th Asia and South Pacific Design Automation Conference, ASPDAC 2019 - Tokyo, 日本
持續時間: 21 01 201924 01 2019

出版系列

名字Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC

Conference

Conference24th Asia and South Pacific Design Automation Conference, ASPDAC 2019
國家/地區日本
城市Tokyo
期間21/01/1924/01/19

文獻附註

Publisher Copyright:
© 2019 Association for Computing Machinery.

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