collaborators

7 papers

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…

cs.AR2025

ATLAS: A Self-Supervised and Cross-Stage Netlist Power Model for Fine-Grained Time-Based Layout Power Analysis

Wenkai Li, Yao Lu, Wenji Fang +3

Accurate power prediction in VLSI design is crucial for effective power optimization, especially as designs get transformed from gate-level netlist to layout stages. However, tradi…

cs.AR2025

AutoPower: Automated Few-Shot Architecture-Level Power Modeling by Power Group Decoupling

Qijun Zhang, Yao Lu, Mengming Li +1

Power efficiency is a critical design objective in modern CPU design. Architects need a fast yet accurate architecture-level power evaluation tool to perform early-stage power esti…

cs.AR2025

Profile-Guided Temporal Prefetching

Mengming Li, Qijun Zhang, Yichuan Gao +4

Temporal prefetching shows promise for handling irregular memory access patterns, which are common in data-dependent and pointer-based data structures. Recent studies introduced on…