activity
20232026
most citedRTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution

95 citations · 113 across the 16 of their papers we have counts for

collaborators

18 papers

cs.AR2026

FABO: Agent-Guided Discovery of Joint Breakpoint Optimization for Timing-Driven Routing Trees

Shang Liu, Wenji Fang, Jing Wang +3

The topology of a routing tree determines how a multi-pin net branches and shares physical wire, directly affecting wirelength, congestion, capacitance, and delay. We study a centr…

cs.CE2026

COOL: A Cooling-Aware Point Transformer Framework for Thermal Prediction in Advanced 3D/3.5D IC Packaging

Yao Lu, Zhicheng Guo, Qijun Zhang +4

Advanced 3D and 3.5D IC packaging significantly improves integration density but elevates thermal management challenges due to cross-layer heat coupling and complex cooling structu…

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.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.SE2025

HLSDebugger: Identification and Correction of Logic Bugs in HLS Code with LLM Solutions

Jing Wang, Shang Liu, Yao Lu +1

High-level synthesis (HLS) accelerates hardware design by enabling the automatic translation of high-level descriptions into efficient hardware implementations. However, debugging…

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…

cs.AR2025

NetTAG: A Multimodal RTL-and-Layout-Aligned Netlist Foundation Model via Text-Attributed Graph

Wenji Fang, Wenkai Li, Shang Liu +3

Circuit representation learning has shown promise in advancing Electronic Design Automation (EDA) by capturing structural and functional circuit properties for various tasks. Exist…

cs.LG2025

GenEDA: Towards Generative Netlist Functional Reasoning via Cross-Modal Circuit Encoder-Decoder Alignment

Wenji Fang, Jing Wang, Yao Lu +2

The success of foundation AI has motivated the research of circuit foundation models, which are customized to assist the integrated circuit (IC) design process. However, existing p…

cs.AR2025

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.AR2024

FirePower: Towards a Foundation with Generalizable Knowledge for Architecture-Level Power Modeling

Qijun Zhang, Mengming Li, Yao lu +1

Power efficiency is a critical design objective in modern processor design. A high-fidelity architecture-level power modeling method is greatly needed by CPU architects for guiding…

cs.PL2023★ 95 cited

RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solution

Shang Liu, Wenji Fang, Yao Lu +3

The automatic generation of RTL code (e.g., Verilog) using natural language instructions and large language models (LLMs) has attracted significant research interest recently. Howe…

cs.AR2023★ 5 cited

MasterRTL: A Pre-Synthesis PPA Estimation Framework for Any RTL Design

Wenji Fang, Yao Lu, Shang Liu +5

In modern VLSI design flow, the register-transfer level (RTL) stage is a critical point, where designers define precise design behavior with hardware description languages (HDLs) l…

cs.LG2023★ 13 cited

RTLLM: An Open-Source Benchmark for Design RTL Generation with Large Language Model

Yao Lu, Shang Liu, Qijun Zhang +1

Inspired by the recent success of large language models (LLMs) like ChatGPT, researchers start to explore the adoption of LLMs for agile hardware design, such as generating design…