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DFGAS: Exploring the Balance of HW-SW Scheduling through the DFG-Aware Scheme 期刊论文
ACM TRANSACTIONS ON ARCHITECTURE AND CODE OPTIMIZATION, 2025, 卷号: 22, 期号: 4, 页码: 26
作者:  Liu, Tianyu;  Fan, Zhihua;  Li, Wenming;  Wang, Zhen;  Qiu, Yuhang;  Tang, Shengzhong;  Wu, Haibin;  Liu, Yanhuan;  Ye, Xiaochun;  Fan, Dongrui
收藏  |  浏览/下载：2/0  |  提交时间：2026/05/25
CGRA  hardware-software co-design  network-on-chip  
CODA: A Computation-Driven Paradigm for Sparse DNN Acceleration 期刊论文
IEEE COMPUTER ARCHITECTURE LETTERS, 2025, 卷号: 24, 期号: 2, 页码: 381-384
作者:  Liu, Yanhuan;  Li, Wenming;  Zhang, Kunming;  Liu, Tianyu;  Ye, Xiaochun;  An, Xuejun
收藏  |  浏览/下载：0/0  |  提交时间：2026/05/25
Software  Hardware  Computational modeling  Sparse matrices  Pipelines  Indexes  Data models  Spatial databases  Computational efficiency  Vectors  Computation-driven architecture  sparse DNN acceleration  dataflow paradigm  unstructured sparsity  work tokenizer  dynamic execution core  asynchronous execution  
DFU-E: A Dataflow Architecture for Edge DSP and AI Applications 期刊论文
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2025, 卷号: 36, 期号: 6, 页码: 1100-1114
作者:  Li, Wenming;  Fan, Zhihua;  Liu, Tianyu;  Wang, Zhen;  Wu, Haibin;  Wu, Meng;  Zhang, Kunming;  Liu, Yanhuan;  Sun, Ninghui;  Ye, Xiaochun;  Fan, Dongrui
收藏  |  浏览/下载：66/0  |  提交时间：2025/06/25
Artificial intelligence  Hardware  Edge computing  Computer architecture  Computational modeling  Single instruction multiple data  Energy efficiency  Target recognition  Radar polarimetry  Real-time systems  Dataflow architecture  edge computing  digital signal processing  AI  multi-layer dataflow mechanism  
Accelerating Convolutional Neural Networks by Exploiting the Sparsity of Output Activation 期刊论文
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2023, 卷号: 34, 期号: 12, 页码: 3253-3265
作者:  Fan, Zhihua;  Li, Wenming;  Wang, Zhen;  Liu, Tianyu;  Wu, Haibin;  Liu, Yanhuan;  Wu, Meng;  Wu, Xinxin;  Ye, Xiaochun;  Fan, Dongrui;  Sun, Ninghui;  An, Xuejun
收藏  |  浏览/下载：67/0  |  提交时间：2024/05/20
Accelerator  output activation  prediction  sparse convolutional neural network