{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T14:02:13Z","timestamp":1774533733060,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":34,"publisher":"ACM","license":[{"start":{"date-parts":[[2018,6,12]],"date-time":"2018-06-12T00:00:00Z","timestamp":1528761600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2018,6,12]]},"DOI":"10.1145\/3204949.3204975","type":"proceedings-article","created":{"date-parts":[[2018,6,27]],"date-time":"2018-06-27T12:22:47Z","timestamp":1530102167000},"page":"204-215","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":75,"title":["Latency and throughput characterization of convolutional neural networks for mobile computer vision"],"prefix":"10.1145","author":[{"given":"Jussi","family":"Hanhirova","sequence":"first","affiliation":[{"name":"Aalto University, Espoo, Finland"}]},{"given":"Teemu","family":"K\u00e4m\u00e4r\u00e4inen","sequence":"additional","affiliation":[{"name":"Aalto University, Espoo, Finland"}]},{"given":"Sipi","family":"Sepp\u00e4l\u00e4","sequence":"additional","affiliation":[{"name":"Aalto University, Espoo, Finland"}]},{"given":"Matti","family":"Siekkinen","sequence":"additional","affiliation":[{"name":"Aalto University, Espoo, Finland"}]},{"given":"Vesa","family":"Hirvisalo","sequence":"additional","affiliation":[{"name":"Aalto University, Espoo, Finland"}]},{"given":"Antti","family":"Yl\u00e4-J\u00e4\u00e4ski","sequence":"additional","affiliation":[{"name":"Aalto University, Espoo, Finland"}]}],"member":"320","published-online":{"date-parts":[[2018,6,12]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Anderson","author":"Amert Tanya","year":"2017","unstructured":"Tanya Amert , Nathan Otterness , Ming Yang , and James H . Anderson . 2017 . GPU Scheduling on the NVIDIA TX2: Hidden Details Revealed Tanya Amert, Nathan Otterness, Ming Yang, and James H. Anderson. 2017. GPU Scheduling on the NVIDIA TX2: Hidden Details Revealed"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2994551.2994564"},{"key":"e_1_3_2_1_3_1","unstructured":"Qualcomm Snapdragon Blog. 2018. TensorFlow machine learning now optimized for the Snapdragon 835 and Hexagon 682 DSP: https:\/\/www.qualcomm.com\/news\/snapdragon\/2017\/01\/09\/tensorflow-machine-learning-now-optimized-snapdragon-835-and-hexagon-682. (2018).  Qualcomm Snapdragon Blog. 2018. TensorFlow machine learning now optimized for the Snapdragon 835 and Hexagon 682 DSP: https:\/\/www.qualcomm.com\/news\/snapdragon\/2017\/01\/09\/tensorflow-machine-learning-now-optimized-snapdragon-835-and-hexagon-682. (2018)."},{"key":"e_1_3_2_1_4_1","volume-title":"Clipper: A Low-Latency Online Prediction Serving System. In 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI\u00e2\u0102&Zacute;17)","author":"Crankshaw Daniel","year":"2017","unstructured":"Daniel Crankshaw , Xin Wang , Guilio Zhou , Michael J. Franklin , Joseph E. Gonzalez , and Ion Stoica . 2017 . Clipper: A Low-Latency Online Prediction Serving System. In 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI\u00e2\u0102&Zacute;17) . 613--627. Daniel Crankshaw, Xin Wang, Guilio Zhou, Michael J. Franklin, Joseph E. Gonzalez, and Ion Stoica. 2017. Clipper: A Low-Latency Online Prediction Serving System. In 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI\u00e2\u0102&Zacute;17). 613--627."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3038228.3038239"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3079856.3080246"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3102980.3102998"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1815961.1816021"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2906388.2906396"},{"key":"e_1_3_2_1_10_1","volume-title":"Learning non-maximum suppression. CoRR abs\/1705.02950","author":"Hosang Jan Hendrik","year":"2017","unstructured":"Jan Hendrik Hosang , Rodrigo Benenson , and Bernt Schiele . 2017. Learning non-maximum suppression. CoRR abs\/1705.02950 ( 2017 ). arXiv:1705.02950 http:\/\/arxiv.org\/abs\/1705.02950 Jan Hendrik Hosang, Rodrigo Benenson, and Bernt Schiele. 2017. Learning non-maximum suppression. CoRR abs\/1705.02950 (2017). arXiv:1705.02950 http:\/\/arxiv.org\/abs\/1705.02950"},{"key":"e_1_3_2_1_11_1","volume-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861","author":"Howard Andrew G","year":"2017","unstructured":"Andrew G Howard , Menglong Zhu , Bo Chen , Dmitry Kalenichenko , Weijun Wang , Tobias Weyand , Marco Andreetto , and Hartwig Adam . 2017 . Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861 (2017). Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam. 2017. Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861 (2017)."},{"key":"e_1_3_2_1_12_1","volume-title":"Speed\/Accuracy Trade-Offs for Modern Convolutional Object Detectors. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Huang Jonathan","year":"2017","unstructured":"Jonathan Huang , Vivek Rathod , Chen Sun , Menglong Zhu , Anoop Korattikara , Alireza Fathi , Ian Fischer , Zbigniew Wojna , Yang Song , Sergio Guadarrama , and Kevin Murphy . 2017 . Speed\/Accuracy Trade-Offs for Modern Convolutional Object Detectors. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Jonathan Huang, Vivek Rathod, Chen Sun, Menglong Zhu, Anoop Korattikara, Alireza Fathi, Ian Fischer, Zbigniew Wojna, Yang Song, Sergio Guadarrama, and Kevin Murphy. 2017. Speed\/Accuracy Trade-Offs for Modern Convolutional Object Detectors. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3081333.3081360"},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the 32nd International Conference on Machine Learning (Proceedings of Machine Learning Research), Francis Bach and David Blei (Eds.)","volume":"37","author":"Ioffe Sergey","year":"2015","unstructured":"Sergey Ioffe and Christian Szegedy . 2015 . Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift . In Proceedings of the 32nd International Conference on Machine Learning (Proceedings of Machine Learning Research), Francis Bach and David Blei (Eds.) , Vol. 37 . PMLR, Lille, France, 448--456. Sergey Ioffe and Christian Szegedy. 2015. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. In Proceedings of the 32nd International Conference on Machine Learning (Proceedings of Machine Learning Research), Francis Bach and David Blei (Eds.), Vol. 37. PMLR, Lille, France, 448--456."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.4108\/eai.30-11-2016.2267463"},{"key":"e_1_3_2_1_16_1","volume-title":"DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices. In 2016 15th ACM\/IEEE International Conference on Information Processing in Sensor Networks (IPSN). 1--12","author":"Lane N. D.","unstructured":"N. D. Lane , S. Bhattacharya , P. Georgiev , C. Forlivesi , L. Jiao , L. Qendro , and F. Kawsar . 2016 . DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices. In 2016 15th ACM\/IEEE International Conference on Information Processing in Sensor Networks (IPSN). 1--12 . N. D. Lane, S. Bhattacharya, P. Georgiev, C. Forlivesi, L. Jiao, L. Qendro, and F. Kawsar. 2016. DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices. In 2016 15th ACM\/IEEE International Conference on Information Processing in Sensor Networks (IPSN). 1--12."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2750858.2804262"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/2964284.2973801"},{"key":"e_1_3_2_1_19_1","volume-title":"Deep learning. Nature 521, 7553","author":"LeCun Yann","year":"2015","unstructured":"Yann LeCun , Yoshua Bengio , and Geoffrey Hinton . 2015. Deep learning. Nature 521, 7553 ( 2015 ), 436--444. Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. Nature 521, 7553 (2015), 436--444."},{"key":"e_1_3_2_1_20_1","volume-title":"DeepCham: Collaborative Edge-Mediated Adaptive Deep Learning for Mobile Object Recognition. In 2016 IEEE\/ACM Symposium on Edge Computing (SEC). 64--76","author":"Li D.","unstructured":"D. Li , T. Salonidis , N. V. Desai , and M. C. Chuah . 2016 . DeepCham: Collaborative Edge-Mediated Adaptive Deep Learning for Mobile Object Recognition. In 2016 IEEE\/ACM Symposium on Edge Computing (SEC). 64--76 . D. Li, T. Salonidis, N. V. Desai, and M. C. Chuah. 2016. DeepCham: Collaborative Edge-Mediated Adaptive Deep Learning for Mobile Object Recognition. In 2016 IEEE\/ACM Symposium on Edge Computing (SEC). 64--76."},{"key":"e_1_3_2_1_21_1","volume-title":"SSD: Single Shot MultiBox Detector. In 14th European Conference on Computer Vision (ECCV","author":"Liu Wei","year":"2016","unstructured":"Wei Liu , Dragomir Anguelov , Dumitru Erhan , Christian Szegedy , Scott Reed , Cheng-Yang Fu , and Alexander C. Berg . 2016 . SSD: Single Shot MultiBox Detector. In 14th European Conference on Computer Vision (ECCV 2016 ). Springer International Publishing, 21--37. Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, and Alexander C. Berg. 2016. SSD: Single Shot MultiBox Detector. In 14th European Conference on Computer Vision (ECCV 2016). Springer International Publishing, 21--37."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3102980.3103003"},{"key":"e_1_3_2_1_23_1","unstructured":"Azalia Mirhoseini Hieu Pham Quoc Le Mohammad Norouzi Samy Bengio Benoit Steiner Yuefeng Zhou Naveen Kumar Rasmus Larsen and Jeff Dean. 2017. Device Placement Optimization with Reinforcement Learning. https:\/\/arxiv.org\/abs\/1706.04972  Azalia Mirhoseini Hieu Pham Quoc Le Mohammad Norouzi Samy Bengio Benoit Steiner Yuefeng Zhou Naveen Kumar Rasmus Larsen and Jeff Dean. 2017. Device Placement Optimization with Reinforcement Learning. https:\/\/arxiv.org\/abs\/1706.04972"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3102980.3102995"},{"key":"e_1_3_2_1_25_1","unstructured":"NVIDIA. 2018. CUDA Multi-Process Service: https:\/\/docs.nvidia.com\/deploy\/mps\/index.html. (2018).  NVIDIA. 2018. CUDA Multi-Process Service: https:\/\/docs.nvidia.com\/deploy\/mps\/index.html. (2018)."},{"key":"e_1_3_2_1_26_1","unstructured":"NVIDIA. 2018. TensorRT: https:\/\/developer.nvidia.com\/tensorrt. (2018).  NVIDIA. 2018. TensorRT: https:\/\/developer.nvidia.com\/tensorrt. (2018)."},{"key":"e_1_3_2_1_27_1","volume-title":"Proceeding of the International Conference on Learning Representations.","author":"Qi Hang","year":"2017","unstructured":"Hang Qi , Evan R. Sparks , and Ameet Talwalkar . 2017 . Paleo: A Performance Model For Deep Neural Networks . In Proceeding of the International Conference on Learning Representations. Hang Qi, Evan R. Sparks, and Ameet Talwalkar. 2017. Paleo: A Performance Model For Deep Neural Networks. In Proceeding of the International Conference on Learning Representations."},{"key":"e_1_3_2_1_28_1","unstructured":"Qualcomm. 2018. Snapdragon Neural Processing Engine SDK: https:\/\/developer.qualcomm.com\/software\/snapdragon-neural-processing-engine. (2018).  Qualcomm. 2018. Snapdragon Neural Processing Engine SDK: https:\/\/developer.qualcomm.com\/software\/snapdragon-neural-processing-engine. (2018)."},{"key":"e_1_3_2_1_29_1","volume-title":"Real-Time Object Detection. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Redmon Joseph","year":"2016","unstructured":"Joseph Redmon , Santosh Divvala , Ross Girshick , and Ali Farhadi . 2016 . You Only Look Once: Unified , Real-Time Object Detection. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi. 2016. You Only Look Once: Unified, Real-Time Object Detection. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"e_1_3_2_1_31_1","volume-title":"Going Deeper With Convolutions. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Szegedy Christian","year":"2015","unstructured":"Christian Szegedy , Wei Liu , Yangqing Jia , Pierre Sermanet , Scott Reed , Dragomir Anguelov , Dumitru Erhan , Vincent Vanhoucke , and Andrew Rabinovich . 2015 . Going Deeper With Convolutions. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, and Andrew Rabinovich. 2015. Going Deeper With Convolutions. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_1_32_1","volume-title":"Rethinking the Inception Architecture for Computer Vision. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Szegedy Christian","year":"2016","unstructured":"Christian Szegedy , Vincent Vanhoucke , Sergey Ioffe , Jon Shlens , and Zbigniew Wojna . 2016 . Rethinking the Inception Architecture for Computer Vision. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna. 2016. Rethinking the Inception Architecture for Computer Vision. In The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/2757384.2757397"},{"key":"e_1_3_2_1_34_1","volume-title":"The 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI'17)","author":"Zhang Haoyu","unstructured":"Haoyu Zhang , Ganesh Ananthanarayanan , Peter Bodik , Matthai Philipose , Victor Bahl , and Michael J. Freedman . 2017. Live Video Analytics at Scale with Approximation and Delay-Tolerance . In The 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI'17) . USENIX, 377--392. Haoyu Zhang, Ganesh Ananthanarayanan, Peter Bodik, Matthai Philipose, Victor Bahl, and Michael J. Freedman. 2017. Live Video Analytics at Scale with Approximation and Delay-Tolerance. In The 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI'17). USENIX, 377--392."}],"event":{"name":"MMSys '18: 9th ACM Multimedia Systems Conference","location":"Amsterdam Netherlands","acronym":"MMSys '18","sponsor":["SIGMM ACM Special Interest Group on Multimedia","SIGCOMM ACM Special Interest Group on Data Communication","SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing","SIGOPS ACM Special Interest Group on Operating Systems"]},"container-title":["Proceedings of the 9th ACM Multimedia Systems Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3204949.3204975","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3204949.3204975","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T01:08:32Z","timestamp":1750208912000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3204949.3204975"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,6,12]]},"references-count":34,"alternative-id":["10.1145\/3204949.3204975","10.1145\/3204949"],"URL":"https:\/\/doi.org\/10.1145\/3204949.3204975","relation":{},"subject":[],"published":{"date-parts":[[2018,6,12]]},"assertion":[{"value":"2018-06-12","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}