I am a PhD student at Department of Electrical and Computer Engineering, UC Santa Barbara, starting from 2020. I work with Prof. Yufei Ding and Prof. Yuan Xie. My research interest is computer architecture. I received my B.E. from Department of Electronic Engineering, Tsinghua University.
[DAC’22][Sparse NN] Guyue Huang, Haoran Li, Minghai Qin, Fei Sun, Yufei Ding and Yuan Xie. Shfl-BW: Accelerating Deep Neural Network Inference with Tensor-Core Aware Weight Pruning. to appear, DAC’22 [code]
[DAC’22][GPU Sparse Kernel] Guohao Dai, Guyue Huang, Shang Yang, Zhongming Yu, Hengrui Zhang, Yufei Ding, Yuan Xie, Huazhong Yang, Yu Wang. Heuristic Adaptability to Input Dynamics for SpMM on GPUs. to appear, DAC’22 (Best Paper Nominee)
[MLSys’22][GNN System] Hengrui Zhang, Zhongming Yu, Guohao Dai, Guyue Huang, Yufei Ding, Yuan Xie, Yu Wang. Understanding GNN Computational Graph: A Coordinated Computation, IO, and Memory Perspective.
[ICCD’21][GPU Sparse Kernel] Zhongming Yu, Guohao Dai, Guyue Huang, Yu Wang and Huazhong Yang. Exploiting Online Locality and Reduction Parallelism for Sampled Dense Matrix Multiplication on GPUs. The 39th IEEE International Conference on Computer Design (ICCD), 2021.
[ACM-SRC’21][GPU Sparse Kernel]Guyue Huang, Guohao Dai, Yu Wang, Yufei Ding and Yuan Xie. Efficient Sparse Matrix Kernels based on Adaptive Workload-Balancing and Parallel-Reduction. 2021. ACM Student Research Competition (SRC), Graduate 3rd Place (https://src.acm.org)
[TODAES’21][ML EDA] Guyue Huang*, Jingbo Hu*, Yifan He*, Jialong Liu*, Mingyuan Ma*, Chaoyang Shen*, Juejian Wu*, Yuanfan Xu*, Hengrui Zhang*, Kai Zhong*, Xuefei Ning, Yuzhe Ma, Haoyu Yang, Bei Yu, Huazhong Yang, and Yu Wang, Machine Learning for Electronic Design Automation: A Survey.
[SC’20][GPU Sparse Kernel] Guyue Huang, Guohao Dai, Yu Wang and Huazhong Yang. GE-SpMM: General-purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks. The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), 2020. [code]
The dgSPARSE project contains high-performance GPU kernels for sparse matrix primitives. We provide an interface to easily replace cuSPARSE in your existing applications. It contains