Rl-sizer: Vlsi gate sizing for timing optimization using deep reinforcement learning

YC Lu, S Nath, V Khandelwal… - 2021 58th ACM/IEEE …, 2021 - ieeexplore.ieee.org
Gate sizing for timing optimization is performed extensively throughout electronic design
automation (EDA) flows. However, increasing design sizes and time-to-market pressure …

Transsizer: A novel transformer-based fast gate sizer

S Nath, G Pradipta, C Hu, T Yang, B Khailany… - Proceedings of the 41st …, 2022 - dl.acm.org
Gate sizing is a fundamental netlist optimization move and researchers have used
supervised learning-based models in gate sizers. Recently, Reinforcement Learning (RL) …

Eco-gnn: Signoff power prediction using graph neural networks with subgraph approximation

YC Lu, S Nath, S Pentapati, SK Lim - ACM Transactions on Design …, 2023 - dl.acm.org
Modern electronic design automation flows depend on both implementation and signoff
tools to perform timing-constrained power optimization through Engineering Change Orders …

DAGSizer: A Directed Graph Convolutional Network Approach to Discrete Gate Sizing of VLSI Graphs

CK Cheng, C Holtz, AB Kahng, B Lin… - ACM Transactions on …, 2023 - dl.acm.org
The objective of a leakage recovery step is to make use of positive slack and reduce power
by performing appropriate standard-cell swaps such as threshold-voltage (Vth) or channel …

A fast learning-driven signoff power optimization framework

YC Lu, S Nath, SSK Pentapati, SK Lim - Proceedings of the 39th …, 2020 - dl.acm.org
Modern high-performance System-on-Chip (SoC) design flows highly depend on signoff
tools to perform timing-constrained power optimization through Engineering Change Orders …

An efficient leakage power optimization framework based on reinforcement learning with graph neural network

P Cao, Y Dong, Z Zhang, W Ding, J Wang - Scientific Reports, 2024 - nature.com
Threshold voltage (V th) assignment is convenient for leakage optimization due to the
exponential relation between leakage power and V th by swap** logic cells without …

Generative self-supervised learning for gate sizing

S Nath, G Pradipta, C Hu, T Yang, B Khailany… - Proceedings of the 59th …, 2022 - dl.acm.org
Self-supervised learning has shown great promise in leveraging large amounts of unlabeled
data to achieve higher accuracy than supervised learning methods in many domains …

Enhancing sensitivity-based power reduction for an industry IC design context

H Fatemi, AB Kahng, H Lee, J Li, JP de Gyvez - Integration, 2019 - Elsevier
For many years, discrete gate sizing has been widely used for timing and power optimization
in VLSI designs. The importance of gate sizing optimization has been emphasized by …

OSFA: A new paradigm of aging aware gate-sizing for power/performance optimizations under multiple operating conditions

S Roy, D Liu, J Singh, J Um… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Modern systems-on-a-chip and microprocessors, eg, those in smart phones and laptops,
typically have multiple operating conditions, such as video streaming, Web browsing …

Efficient and Accurate ECO Leakage Optimization Framework With GNN and Bidirectional LSTM

P Cao, G He, W Ding, Z Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Engineering change order (ECO) plays an important role in design flow to perform leakage
optimization with gate-sizing and assignment approaches. Unfortunately, it is extremely time …