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20212026
most citedExplainable Fuzzy Neural Network with Multi-Fidelity Reinforcement Learning for Micro-Architecture Design Space Exploration

1 citations · 2 across the 7 of their papers we have counts for

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cs.AR2026

APEX-RBD: Mixed-Precision Exploration Framework for Hardware-Efficient Robot Dynamics Accelerator Design

Xingyu Liu, Hanwei Fan, Chaofang Ma +4

Rigid Body Dynamics (RBD) forms the computational core of real-time robotic control, but its immense computational complexity creates a performance bottleneck that necessitates ded…

cs.AR2026

ThermoDSE: A Thermal-Aware and Comprehensive Design Space Exploration for Chiplet-Based DNN Accelerators

Jian Peng, Hanwei Fan, Jingbo Jiang +2

Chiplet-based DNN accelerators provide a scalable path to balance performance and yield for modern AI workloads. However, such systems face critical challenges in area and thermal…

cs.AR2026

HiFuzz: Hierarchical Reinforcement Learning for Semantic-Aware and Adaptive CPU Fuzzing

Ya Wang, Hanwei Fan, Zhenguo Liu +4

Modern processor verification struggles to reach deep architectural states due to the inefficiencies of traditional mutation-based fuzzing. We propose HiFuzz, a novel hierarchical…

cs.AR2026

FPPS: An FPGA-Based Point Cloud Processing System

Xiaofeng Zhou, Linfeng Du, Hanwei Fan +1

Point cloud processing is a computational bottleneck in autonomous driving systems, especially for real-time applications, while energy efficiency remains a critical system constra…

cs.AR2025

FLEX: Leveraging FPGA-CPU Synergy for Mixed-Cell-Height Legalization Acceleration

Xingyu Liu, Jiawei Liang, Linfeng Du +5

In this work, we present FLEX, an FPGA-CPU accelerator for mixed-cell-height legalization tasks. We address challenges from the following perspectives. First, we optimize the task…