Rl-sizer: Vlsi gate sizing for timing optimization using deep reinforcement learning
Gate sizing for timing optimization is performed extensively throughout electronic design
automation (EDA) flows. However, increasing design sizes and time-to-market pressure …
automation (EDA) flows. However, increasing design sizes and time-to-market pressure …
Transsizer: A novel transformer-based fast gate sizer
Gate sizing is a fundamental netlist optimization move and researchers have used
supervised learning-based models in gate sizers. Recently, Reinforcement Learning (RL) …
supervised learning-based models in gate sizers. Recently, Reinforcement Learning (RL) …
Eco-gnn: Signoff power prediction using graph neural networks with subgraph approximation
Modern electronic design automation flows depend on both implementation and signoff
tools to perform timing-constrained power optimization through Engineering Change Orders …
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
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 …
by performing appropriate standard-cell swaps such as threshold-voltage (Vth) or channel …
A fast learning-driven signoff power optimization framework
Modern high-performance System-on-Chip (SoC) design flows highly depend on signoff
tools to perform timing-constrained power optimization through Engineering Change Orders …
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 …
exponential relation between leakage power and V th by swap** logic cells without …
Generative self-supervised learning for gate sizing
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 …
data to achieve higher accuracy than supervised learning methods in many domains …
Enhancing sensitivity-based power reduction for an industry IC design context
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 …
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
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 …
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 …
optimization with gate-sizing and assignment approaches. Unfortunately, it is extremely time …