Maohua Zhu

发表

Implementation and evaluation of deep neural networks (DNN) on mainstream heterogeneous systems

Zhen Lin, Feng Zhang, Maohua Zhu, 2014, APSys.

Sparse Tensor Core: Algorithm and Hardware Co-Design for Vector-wise Sparse Neural Networks on Modern GPUs

Yuan Xie, Zhenyu Gu, Tao Zhang, 2019, MICRO.

Tianjic: A Unified and Scalable Chip Bridging Spike-Based and Continuous Neural Computation

Wei He, Luping Shi, Jing Pei, 2020, IEEE Journal of Solid-State Circuits.

Dynamic Sparse Graph for Efficient Deep Learning pdf

Liu Liu, Lei Deng, Guoqi Li, 2018, ICLR.

Training Long Short-Term Memory With Sparsified Stochastic Gradient Descent

Yuan Xie, Jason Clemons, Stephen W. Keckler, 2017 .

Performance Evaluation and Optimization of HBM-Enabled GPU for Data-Intensive Applications

Wenguang Chen, Chao Wang, Yuan Xie, 2017, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

fuseGNN: Accelerating Graph Convolutional Neural Network Training on GPGPU

Lei Deng, Mingyu Yan, Shuangchen Li, 2020, 2020 IEEE/ACM International Conference On Computer Aided Design (ICCAD).

CNNLab: a Novel Parallel Framework for Neural Networks using GPU and FPGA-a Practical Study with Trade-off Analysis pdf

Liu Liu, Chao Wang, Yuan Xie, 2016, ArXiv.

OpenCL caffe: Accelerating and enabling a cross platform machine learning framework

Yibing Liu, Yuan Gao, Maohua Zhu, 2016, IWOCL.

Taming Unstructured Sparsity on GPUs via Latency-Aware Optimization

Yuan Xie, Maohua Zhu, Yuan Xie, 2020, 2020 57th ACM/IEEE Design Automation Conference (DAC).

Evaluating the potential of graphics processors for high performance embedded computing

Yangdong Deng, Shuai Mu, Ming Liu, 2011, 2011 Design, Automation & Test in Europe.