个人简介 :

李钢，中科院自动化所复杂系统认知与决策实验室副研究员。2013年于西北工业大学自动化学院获得学士学位。2018年和2021年于中科院自动化所分别获得硕士和博士学位。2021年9月至2024年7月在上海交通大学电子信息与电气工程学院从事博士后研究。主要从事计算机体系结构、深度学习方面的研究。在MICRO、HPCA、ASPLOS、TCAD、DAC、DATE、TCAS-II、TNNLS、ICCV、ECCV、ACL、AAAI、ICLR等国际顶级会议和期刊发表论文近30篇，获得DATE’23和DATE’24最佳论文奖，以及DATE’21最佳论文提名。博士期间兼任中科南京人工智能创新研究院芯片总架构师，带队成功研发了量化神经处理器芯片QNPU。

发表论文 :

• Zeyu Zhu, Fanrong Li, Gang Li, Zejian Liu, Zitao Mo, Qinghao Hu, Xiaoyao Liang, Jian Cheng. MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization. HPCA 2024 (CCF-A，通讯作者)
• Zeyu Zhu, Peisong Wang, Qinghao Hu, Gang Li, Xiaoyao Liang, Jian Cheng. FastGL: A GPU-Efficient Framework for Accelerating Sampling-Based GNN Training at Large Scale. ASPLOS 2024 (CCF-A)
• Xueyuan Liu, Zhuoran Song, Guohao Dai, Gang Li, Can Xiao, Yan Xiang, Dehui Kong, Ke Xu, and Xiaoyao Liang. FusionArch: A Fusion-Based Accelerator for Point-Based Point Cloud Neural Networks. DATE 2024 (CCF-B，最佳论文)
• Xiaolong Lin, Gang Li, Zizhao Liu, Yadong Liu, Fan Zhang, Zhuoran Song, Naifeng Jing, Xiaoyao Liang. AdaS: A Fast and Energy-Efficient CNN Accelerator Exploiting Bit-Sparsity. DAC 2023 (CCF-A，通讯作者)
• Zhuoran Song, Heng Lu, Gang Li, Li Jiang, Naifeng Jing, Xiaoyao Liang. PRADA: Point Cloud Recognition Acceleration via Dynamic Approximation. DATE 2023 (CCF-B，最佳论文)
• Qinghao Hu, Gang Li, Qiman Wu, Jian Cheng. PalQuant: Accelerating High-Precision Networks on Low-Precision Accelerators. ECCV 2022 (CCF-B，共同一作)
• Gang Li, Weixiang Xu, Zhuoran Song, Naifeng Jing, Jian Cheng, Xiaoyao Liang. Ristretto: An Atomized Processing Architecture for Sparsity-Condensed Stream Flow in CNN. MICRO 2022 (CCF-A)
• Gang Li, Zejian Liu, Fanrong Li, Jian Cheng. Block Convolution: Towards Memory-Efficient Inference of Large-Scale CNNs on FPGA. TCAD 2021 (CCF-A)
• Zejian Liu, Gang Li, Jian Cheng. Hardware Acceleration of Fully Quantized BERT for Efficient Natural Language Processing. DATE 2021 (CCF-B，最佳论文提名)
• Gang Li, Peisong Wang, Zejian Liu, Cong Leng, Jian Cheng. Hardware Acceleration of CNN with One-Hot Quantization of Weights and Activations. DATE 2020 (CCF-B)
• Gang Li, Fanrong Li, Tianli Zhao, Jian Cheng. Block Convolution: Towards Memory-Efficient Inference of Large-Scale CNNs on FPGA. DATE 2018 (CCF-B)
• Jian Cheng, Peisong Wang, Gang Li, Qinghao Hu, Hanqing Lu. Recent Advances in Efficient Computation of Deep Convolutional Neural Networks. FITEE 2018 (CCF-C)

获奖情况 :

• DATE’24最佳论文
• DATE’23最佳论文
• DATE’21最佳论文提名