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GPU.bib
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% == this file is about GPU related works
% =========================================
% GPU Scheduling
% =========================================
% === general scheduling
% === DNN scheduling
@inproceedings{GPU-MobiSys2016-MCDNN,
title = {{MCDNN}: An approximation-based execution framework for deep stream processing under resource constraints},
author = {Han, Seungyeop and Shen, Haichen and Philipose, Matthai and Agarwal, Sharad and Wolman, Alec and Krishnamurthy, Arvind},
booktitle = mobisys,
pages = {123--136},
year = {2016},
}
@inproceedings{GPU-RTAS2018-S3DNN,
title = {{S$^3$DNN}: Supervised Streaming and Scheduling for {GPU}-Accelerated Real-Time {DNN} Workloads},
author = {H. Zhou and S. Bateni and C. Liu},
booktitle = rtas,
pages = {190--201},
year = {2018},
}
@inproceedings{GPU-RTSS2018-ApNet,
title = {{ApNet}: Approximation-Aware Real-Time Neural Network},
author = {Bateni, Soroush and Liu, Cong},
booktitle = rtss,
pages = {67--79},
year = {2018},
}
@inproceedings{GPU-MMSys2018-Hanhirova,
title = {Latency and throughput characterization of convolutional neural networks for mobile computer vision},
author = {Hanhirova, Jussi and K{\"a}m{\"a}r{\"a}inen, Teemu and Sepp{\"a}l{\"a}, Sipi and Siekkinen, Matti and Hirvisalo, Vesa and Yl{\"a}-J{\"a}{\"a}ski, Antti},
booktitle = mmsys,
pages = {204--215},
year = {2018},
}
@inproceedings{GPU-PPoPP2018-SuperNeurons,
title = {{SuperNeurons}: dynamic {GPU} memory management for training deep neural networks},
author = {Wang, Linnan and Ye, Jinmian and Zhao, Yiyang and Wu, Wei and Li, Ang and Song, Shuaiwen Leon and Xu, Zenglin and Kraska, Tim},
booktitle = ppopp,
pages = {41--53},
year = {2018},
}
@inproceedings{GPU-RTAS2019-Yang,
title = {Re-thinking {CNN} Frameworks for Time-Sensitive Autonomous-Driving Applications: Addressing an Industrial Challenge},
author = {Yang, Ming and Wang, Shige and Bakita, Joshua and Vu, Thanh and Smith, F Donelson and Anderson, James H and Frahm, Jan-Michael},
booktitle = rtas,
year = {2019},
}