Title
Design Optimization by Fine-grained Interleaving of Local Netlist Transformations in Lagrangian Relaxation
Abstract
Design optimization modifies a netlist with the goal of satisfying the timing constraints at the minimum area and leakage power, without violating any slew or load capacitance constraints. Lagrangian relaxation (LR) based optimization has been established as a viable approach for this. We extend LR-based optimization by interleaving in each iteration techniques such as: gate and flip-flop sizing; buffering to fix late and early timing violations; pin swapping; and useful clock skew. Locally optimal decisions are made using LR-based cost functions, without the need for incremental timing updates. Sub-steps are applied in a balanced manner, accounting for the expected savings and any conflicting timing violations, maximizing the final quality of results under multiple process/operating corners with a reasonable runtime. Experimental results show that our approach achieves better timing, and both lower area and leakage power than the winner of the TAU 2019 contest, on those benchmarks.
Year
DOI
Venue
2020
10.1145/3372780.3375566
ISPD '20: International Symposium on Physical Design Taipei Taiwan September, 2020
DocType
ISBN
Citations 
Conference
978-1-4503-7091-2
0
PageRank 
References 
Authors
0.34
0
5