4 citations · 5 across the 6 of their papers we have counts for
6 papers
LongRTL: Graph-Similarity-Guided LLM-driven Long Context RTL Optimization
Yuyang Ye, Che-Kuan Shen, Xiangfei Hu +5
Large Language Models (LLMs) show great promise in RTL code generation and optimization. However, real-world RTL designs are typically long, entangled, and poorly modularized, posi…
CPPL: A Circuit Prompt Programming Language
Shuo Yin, Yihe Wang, Lancheng Zou +6
Large language models (LLMs) have shown promise in register-transfer level (RTL) design automation, but direct RTL generation remains difficult to validate, optimize, and integrate…
PipeRTL: Timing-Aware Pipeline Optimization at IR-Level for RTL Generation
Shuo Yin, Fangzhou Liu, Lancheng Zou +6
Modern hardware compilers increasingly rely on rich intermediate representations (IRs) to preserve optimization-relevant semantics before generating RTL code. However, one importan…
PermLLM: Learnable Channel Permutation for N:M Sparse Large Language Models
Lancheng Zou, Shuo Yin, Zehua Pei +3
Channel permutation is a powerful technique for enhancing the accuracy of N:M sparse models by reordering the channels of weight matrices to prioritize the retention of important w…
TorchResist: Open-Source Differentiable Resist Simulator
Zixiao Wang, Jieya Zhou, Su Zheng +5
Recent decades have witnessed remarkable advancements in artificial intelligence (AI), including large language models (LLMs), image and video generative models, and embodied AI sy…
SoC-Tuner: An Importance-guided Exploration Framework for DNN-targeting SoC Design
Shixin Chen, Su Zheng, Chen Bai +4
Designing a system-on-chip (SoC) for deep neural network (DNN) acceleration requires balancing multiple metrics such as latency, power, and area. However, most existing methods ign…