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@inproceedings{Rawat:2016:ERM:2884045.2884047, author = {Rawat, Prashant Singh and Hong, Changwan and Ravishankar, Mahesh and Grover, Vinod and Pouchet, Louis-Noël and Sadayappan, P.}, title = {Effective Resource Management for Enhancing Performance of 2D and 3D Stencils on GPUs}, booktitle = {Proceedings of the 9th Annual Workshop on General Purpose Processing Using Graphics Processing Unit}, series = {GPGPU '16}, year = {2016}, isbn = {978-1-4503-4195-0}, location = {Barcelona, Spain}, pages = {92–102}, numpages = {11}, url = {http://doi.acm.org/10.1145/2884045.2884047}, doi = {10.1145/2884045.2884047}, acmid = {2884047}, publisher = {ACM}, address = {New York, NY, USA}, keywords = {GPGPU, resource management, stencil computations, tiling}, }
@article{DBLP:journals/corr/abs-1805-02566,
author = {Hyoukjun Kwon and Michael Pellauer and Tushar Krishna}, 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}
}
@inproceedings{Stock:2014:FED:2594291.2594342, author = {Stock, Kevin and Kong, Martin and Grosser, Tobias and Pouchet, Louis-Noël and Rastello, Fabrice and Ramanujam, J. and Sadayappan, P.}, title = {A Framework for Enhancing Data Reuse via Associative Reordering}, booktitle = {Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation}, series = {PLDI '14}, year = {2014}, isbn = {978-1-4503-2784-8}, location = {Edinburgh, United Kingdom}, pages = {65–76}, numpages = {12}, url = {http://doi.acm.org/10.1145/2594291.2594342}, doi = {10.1145/2594291.2594342}, acmid = {2594342}, publisher = {ACM}, 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},}