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author = {Hyoukjun Kwon and
Michael Pellauer and
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title = {Understanding Reuse, Performance, and Hardware Cost of DNN Dataflows: A Data-Centric Approach},
journal = {CoRR},
volume = {abs/1805.02566},
year = {2018},
url = {http://arxiv.org/abs/1805.02566},
archivePrefix = {arXiv},
eprint = {1805.02566},
timestamp = {Mon, 13 Aug 2018 16:46:45 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/abs-1805-02566},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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@article{Vasilache:2019:NAL:3366460.3355606, author = {Vasilache, Nicolas and Zinenko, Oleksandr and Theodoridis, Theodoros and Goyal, Priya and Devito, Zachary and Moses, William S. and Verdoolaege, Sven and Adams, Andrew and Cohen, Albert}, title = {The Next 700 Accelerated Layers: From Mathematical Expressions of Network Computation Graphs to Accelerated GPU Kernels, Automatically}, journal = {ACM Trans. Archit. Code Optim.}, issue_date = {October 2019}, volume = {16}, number = {4}, month = oct, year = {2019}, issn = {1544-3566}, pages = {38:1–38:26}, articleno = {38}, numpages = {26}, url = {http://doi.acm.org/10.1145/3355606}, doi = {10.1145/3355606}, acmid = {3355606}, publisher = {ACM}, address = {New York, NY, USA}, keywords = {Deep learning layers, GPU acceleration, polyhedral compilation},
