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Maohua Zhu
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Sparse tensor core: Algorithm and hardware co-design for vector-wise sparse neural networks on modern gpus
M Zhu, T Zhang, Z Gu, Y Xie
Proceedings of the 52nd Annual IEEE/ACM International Symposium on …, 2019
1432019
Tianjic: A unified and scalable chip bridging spike-based and continuous neural computation
L Deng, G Wang, G Li, S Li, L Liang, M Zhu, Y Wu, Z Yang, Z Zou, J Pei, ...
IEEE Journal of Solid-State Circuits 55 (8), 2228-2246, 2020
1272020
Dynamic sparse graph for efficient deep learning
L Liu, L Deng, X Hu, M Zhu, G Li, Y Ding, Y Xie
arXiv preprint arXiv:1810.00859, 2018
592018
Performance evaluation and optimization of HBM-Enabled GPU for data-intensive applications
M Zhu, Y Zhuo, C Wang, W Chen, Y Xie
2017 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017
452017
Opencl caffe: Accelerating and enabling a cross platform machine learning framework
J Gu, Y Liu, Y Gao, M Zhu
Proceedings of the 4th International Workshop on OpenCL, 1-5, 2016
402016
Evaluating the potential of graphics processors for high performance embedded computing
S Mu, C Wang, M Liu, D Li, M Zhu, X Chen, X Xie, Y Deng
2011 Design, Automation & Test in Europe, 1-6, 2011
382011
Implementation and evaluation of deep neural networks (DNN) on mainstream heterogeneous systems
J Gu, M Zhu, Z Zhou, F Zhang, Z Lin, Q Zhang, M Breternitz
Proceedings of 5th Asia-Pacific Workshop on Systems, 1-7, 2014
352014
Structurally sparsified backward propagation for faster long short-term memory training
M Zhu, J Clemons, J Pool, M Rhu, SW Keckler, Y Xie
arXiv preprint arXiv:1806.00512, 2018
26*2018
Cnnlab: a novel parallel framework for neural networks using gpu and fpga-a practical study with trade-off analysis
M Zhu, L Liu, C Wang, Y Xie
arXiv preprint arXiv:1606.06234, 2016
252016
fuseGNN: Accelerating graph convolutional neural network training on GPGPU
Z Chen, M Yan, M Zhu, L Deng, G Li, S Li, Y Xie
Proceedings of the 39th International Conference on Computer-Aided Design, 1-9, 2020
202020
Taming unstructured sparsity on GPUs via latency-aware optimization
M Zhu, Y Xie
2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020
102020
A polyhedral modeling based source-to-source code optimization framework for GPGPU
C Wang, K Kang, M Zhu, Y Deng
2012 IEEE 26th International Parallel and Distributed Processing Symposium …, 2012
22012
Efficient Weighted Histogramming on GPUs with HASH
M Zhu, N Xu, CZ Di Wu, Y Deng, Y Wang, FH Hsu
INVITED SPEAKER: Analyzing the Performance of Top-K Retrieval Algorithms, 1995, 0
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Articles 1–13