7 papers
Harvesting AI Computation at the Edge via Generic Approximation
Yihan Wang, Huiru Yan, Luxin Zhang +6
With the widespread adoption of AI in various IoT scenarios such as smart sensing and processing, AI chips have become a common component at the edge. These chips are typically spe…
VeriPilot: An LLM-Powered Verilog Debugging Framework
Yihan Wang, Cheng Liu, Jiazheng Zhang +4
Verilog debugging remains one of the most time-consuming stages in digital circuit design. Recent advances in Large Language Models (LLMs) have enabled automated debugging; however…
ANNS-AMP: Accelerating Approximate Nearest Neighbor Search via Adaptive Mixed-Precision Computing
Mingkai Chen, Cheng Liu, Shengwen Liang +3
Approximate nearest neighbor search(ANNS) is a critical kernel in modern applications such as LLM and recommendation systems.However,its efficiency is fundamentally limited by the…
FT-Pilot: Automated Fault-Tolerant RTL Rewriting via Vulnerability-Guided LLMs
Weixing Liu, Zizhen Liu, Jing Ye +4
As integrated circuit technologies continue to scale toward advanced process nodes, the continual reduction in node capacitance and supply voltage has made digital systems increasi…
Understanding and Mitigating Errors of LLM-Generated RTL Code
Jiazheng Zhang, Cheng Liu, Long Cheng +2
Despite limited success in large language model (LLM)-based register-transfer-level (RTL) code generation, the root causes of errors remain poorly understood. To address this, we c…
From Large to Small: Transferring CUDA Optimization Expertise via Reasoning Graph
Junfeng Gong, Zhiyi Wei, Junying Chen +2
Despite significant evolution of CUDA programming and domain-specific libraries, effectively utilizing GPUs with massively parallel engines remains difficult. Large language models…