collaborators

13 papers

cs.AR2026

G-Power: Architecture-level GPU Power Modeling with Aggregated Knowledge Foundations from Known GPUs

Qijun Zhang, Yao Lu, Shang Liu +4

Graphics Processing Units (GPUs) have been serving as critical computation resources for large-scale parallel computations. With increasing chip complexity, power efficiency has be…

cs.AR2026

LEAP: A Self-Supervised Per-Cycle Toggle Propagation Model Supports Fast, Transferable, and Early Analysis of Layout Power

Wenkai Li, Yuchao Wu, Ziyan Guo +4

Accurate power analysis is critical in VLSI design, as it directly impacts power optimization strategies. However, traditional approaches are often hindered by the substantial runt…

cs.AR2026

A Survey of Circuit Foundation Model: Foundation AI Models for VLSI Circuit Design and EDA

Wenji Fang, Jing Wang, Yao Lu +4

Artificial intelligence (AI)-driven electronic design automation (EDA) techniques have been extensively explored for VLSI circuit design applications. Most recently, foundation AI…

cs.AI2026

A New Benchmark for the Appropriate Evaluation of RTL Code Optimization

Yao Lu, Shang Liu, Hangan Zhou +3

The rapid progress of artificial intelligence increasingly relies on efficient integrated circuit (IC) design. Recent studies have explored the use of large language models (LLMs)…

cs.AR2025

ReadyPower: A Reliable, Interpretable, and Handy Architectural Power Model Based on Analytical Framework

Qijun Zhang, Shang Liu, Yao Lu +2

Power is a primary objective in modern processor design, requiring accurate yet efficient power modeling techniques. Architecture-level power models are necessary for early power o…

cs.AR2025

ArchPower: Dataset for Architecture-Level Power Modeling of Modern CPU Design

Qijun Zhang, Yao Lu, Mengming Li +2

Power is the primary design objective of large-scale integrated circuits (ICs), especially for complex modern processors (i.e., CPUs). Accurate CPU power evaluation requires design…