Acorns: A Framework for Accelerating Deep Neural Networks with Input Sparsity-Reference-Cited by-同舟云学术

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Acorns: A Framework for Accelerating Deep Neural Networks with Input Sparsity

Published:2019-09 Issue: Volume: Page:
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Container-title:2019 28th International Conference on Parallel Architectures and Compilation Techniques (PACT)
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Author:

Dong Xiao,Liu Lei,Zhao Peng,Li Guangli,Li Jiansong,Wang Xueying,Feng Xiaobing

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8890589/8891061/08891649.pdf?arnumber=8891649

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. VTensor: Using Virtual Tensors to Build a Layout-Oblivious AI Programming Framework;Journal of Computer Science and Technology;2023-09

2. Hardware Accelerator Design for Sparse DNN Inference and Training: A Tutorial;IEEE Transactions on Circuits and Systems II: Express Briefs;2023

3. Energy-Efficient Deep Neural Network Optimization via Pooling-Based Input Masking;2022 International Joint Conference on Neural Networks (IJCNN);2022-07-18

4. A data-centric optimization framework for machine learning;Proceedings of the 36th ACM International Conference on Supercomputing;2022-06-28

5. Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights;Proceedings of the IEEE;2021-10

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