Open Access
Issue |
MATEC Web Conf.
Volume 336, 2021
2020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
|
|
---|---|---|
Article Number | 04019 | |
Number of page(s) | 8 | |
Section | Communication Technology | |
DOI | https://doi.org/10.1051/matecconf/202133604019 | |
Published online | 15 February 2021 |
- Tianqi Chen, Thierry M, Ziheng Jiang,et al. TVM: an automated end-to-end optimizing compiler for deep learing[C] // In Proceedings of the 12th USENIX conference on Operating Systems Design and Implementation (OSDI’18). USENIX Association, USA, 2018:579-594. [Google Scholar]
- Jared Roesch, Steven Lyubomirsky, Logan Weber, et al. Relay: a new IR for machine learning frameworks. In Proceedings of the 2nd ACM SIGPLAN International Workshop on Machine Learning and Programming Languages (MAPL 2018). Association for Computing Machinery, New York, NY, USA, 2018:58-68. [Google Scholar]
- Chris Lattner,Vikram Adve. LLVM: A compilation framework for lifelong program analysis & transformation. In Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization. IEEE Computer Society, 2 004:75. [Google Scholar]
- Tianqi Chen, Lianmin Zheng, Eddie Yan,et al. Learning to optimize tensor programs. In Proceedings of the 32nd International Conference on Neural Information Processing Systems (NIPS’18). Curran Associates Inc., Red Hook, NY, USA, 2018: 3393-3404 [Google Scholar]
- Adam Paszke, Sam Gross, Francisco Massa,et al. PyTorch: An imperative style, high-performance deep learning library. In Advances in Neural Information Processing Systems,2019: 8024-8035. [Google Scholar]
- Martín Abadi, Paul Barham, Jianmin Chen, et al. Tensorflow: A system for large-scale machine learning. In 12th {USENIX} Symposium on Operating Systems Design and Implementation ({OSDI} 16),2016:265-283. [Google Scholar]
- Jonathan R.K, Connelly B, Andrew A, et al. Halide: a language and compiler for optimizing parallelism, locality, and recomputation in image processing pipelines[J]. SIGPLAN Not. 48, 2013:519-530. [Google Scholar]
- D.N. Parikh, J Huang, M.E. Myers, et al. Learning from Optimizing Matrix-Matrix Multiplication[C] // 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Vancouver, BC, 2018 [Google Scholar]
- Li Mingzhen, Liu Yi, Liu Xiaoyan, et al. The Deep Learning Compiler: A Comprehensive Survey[J]. 2020 [Google Scholar]
- Sihang Zhou, Xinwang Liu, Miaomiao Li, et al. Multiple Kernel Clustering With Neighbor-Kernel Subspace Segmentation. IEEE Trans Neural Netw Learn Syst. 2020 Apr;31(4):1351-1362. doi: 10.1109/TNNLS.2019.2919900. Epub 2019 Jun 28. PMID: 31265409. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.