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--- melange:papers:fall2019 [2019/10/09 12:07]
jana
+++ melange:papers:fall2019 [2019/10/30 13:51]
jana
@@ Line 18: / Line 18: @@
-@ARTICLE{2018arXiv180502566K,
-       author = {{Kwon}, Hyoukjun and {Chatarasi}, Prasanth and {Pellauer}, Michael and
-         {Parashar}, Angshuman and {Sarkar}, Vivek and {Krishna}, Tushar},
+@article{DBLP:journals/corr/abs-1805-02566,
-        title = "{Understanding Reuse, Performance, and Hardware Cost of DNN Dataflows: A Data-Centric Approach}",
+  author    = {Hyoukjun Kwon and
-      journal = {arXiv e-prints},
+               Michael Pellauer and
-     keywords = {Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Machine Learning},
+               Tushar Krishna},
-         year = "2018",
+  title     = {Understanding Reuse, Performance, and Hardware Cost of DNN Dataflows: A Data-Centric Approach},
-        month = "May",
+  journal   = {CoRR},
-          eid = {arXiv:1805.02566},
+  volume    = {abs/1805.02566},
-        pages = {arXiv:1805.02566},
+  year      = {2018},
-archivePrefix = {arXiv},
+  url       = {http://arxiv.org/abs/1805.02566},
-       eprint = {1805.02566},
+  archivePrefix = {arXiv},
- primaryClass = {cs.DC},
+  eprint    = {1805.02566},
-       adsurl = {https://ui.adsabs.harvard.edu/abs/2018arXiv180502566K},
+  timestamp = {Mon, 13 Aug 2018 16:46:45 +0200},
-      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
+  biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1805-02566},
+  bibsource = {dblp computer science bibliography, https://dblp.org}
 }
@@ Line 53: / Line 55: @@
  address = {New York, NY, USA},
 }
+@ARTICLE{7738524, author={Y. H. Chen and T. Krishna and J. S. Emer and V. Sze}, journal={IEEE Journal of Solid-State Circuits}, title={Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks}, year={2017}, volume={52}, number={1}, pages={127-138}, url = {http://ieeexplore.ieee.org/document/7738524/}, doi={10.1109/JSSC.2016.2616357}, ISSN={0018-9200}, month={Jan},}

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