{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,31]],"date-time":"2024-08-31T06:33:59Z","timestamp":1725086039554},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J. Comput. Sci. Technol."],"published-print":{"date-parts":[[2020,3]]},"DOI":"10.1007\/s11390-020-9686-z","type":"journal-article","created":{"date-parts":[[2020,5,21]],"date-time":"2020-05-21T13:02:47Z","timestamp":1590066167000},"page":"475-489","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["SIES: A Novel Implementation of Spiking Convolutional Neural Network Inference Engine on Field-Programmable Gate Array"],"prefix":"10.1007","volume":"35","author":[{"given":"Shu-Quan","family":"Wang","sequence":"first","affiliation":[]},{"given":"Lei","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yu","family":"Deng","sequence":"additional","affiliation":[]},{"given":"Zhi-Jie","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Sha-Sha","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Zi-Yang","family":"Kang","sequence":"additional","affiliation":[]},{"given":"Yu-Feng","family":"Guo","sequence":"additional","affiliation":[]},{"given":"Wei-Xia","family":"Xu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,3,27]]},"reference":[{"issue":"10","key":"9686_CR1","doi-asserted-by":"crossref","first-page":"1537","DOI":"10.1109\/TCAD.2015.2474396","volume":"34","author":"F Akopyan","year":"2015","unstructured":"Akopyan F, Sawada J, Cassidy A, Alvarez-Icaza R, Arthur J, Merolla P, Imam N, Nakamura Y, Datta P, Nam G J. TrueNorth: Design and tool flow of a 65mW 1 million neuron programmable neurosynaptic chip. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2015, 34(10): 1537-1557.","journal-title":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"},{"key":"9686_CR2","unstructured":"Geddes J, Lloyd S, Simpson A C et al. NeuroGrid: Using grid technology to advance neuroscience. In Proc. the 18th IEEE Symposium on Computer-Based Medical Systems, June 2005, pp.570-572."},{"key":"9686_CR3","doi-asserted-by":"crossref","unstructured":"Schemmel J, Gr\u00fcbl A, Hartmann S et al. Live demonstration: A scaled-down version of the BrainScaleS wafer-scale neuromorphic system. In Proc. the 2012 IEEE International Symposium on Circuits Systems, May 2012, p.702.","DOI":"10.1109\/ISCAS.2012.6272131"},{"issue":"12","key":"9686_CR4","doi-asserted-by":"crossref","first-page":"2454","DOI":"10.1109\/TC.2012.142","volume":"62","author":"SB Furber","year":"2013","unstructured":"Furber S B, Lester D R, Plana L A, Garside J D, Painkras E, Temple S, Brown A D. Overview of the spiNNaker system architecture. IEEE Transactions on Computers, 2013, 62(12): 2454-2467.","journal-title":"IEEE Transactions on Computers"},{"issue":"1","key":"9686_CR5","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1109\/MM.2018.112130359","volume":"38","author":"M Davies","year":"2018","unstructured":"Davies M, Jain S, Liao Y et al. Loihi: A neuromorphic manycore processor with on-chip learning. IEEE Micro, 2018, 38(1): 82-99.","journal-title":"IEEE Micro"},{"key":"9686_CR6","doi-asserted-by":"crossref","unstructured":"Diehl P U, Neil D, Binas J, Cook M, Liu S C, Pfeiffer M. Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing. In Proc. the 2015 International Joint Conference on Neural Networks, July 2015.","DOI":"10.1109\/IJCNN.2015.7280696"},{"key":"9686_CR7","doi-asserted-by":"crossref","unstructured":"Rueckauer B, Lungu I A, Hu Y, Pfeiffer M, Liu S C. Conversion of continuous-valued deep networks to efficient event-driven networks for image classification. Frontiers in Neuroscience, 2017, 11: Article No. 682.","DOI":"10.3389\/fnins.2017.00682"},{"key":"9686_CR8","unstructured":"Rueckauer B, Lungu L A, Hu Y H, Pfeiffer M. Theory and tools for the conversion of analog to spiking convolutional neural networks. arXiv: 1612.04052, 2016. https:\/\/arxiv.org\/pdf\/1612.04052.pdf, Nov. 2019."},{"issue":"3S","key":"9686_CR9","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1145\/2872887.2750389","volume":"43","author":"Zidong Du","year":"2016","unstructured":"Du Z D, Fasthuber R, Chen T S, Ienne P, Li L, Luo T, Feng X B, Chen Y J, Temam O. ShiDianNao: Shifting vision processing closer to the sensor. In Proc. the 42nd ACM\/IEEE International Symposium on Computer Architecture, June 2015, pp.92-104.","journal-title":"ACM SIGARCH Computer Architecture News"},{"key":"9686_CR10","doi-asserted-by":"crossref","unstructured":"Guan Y J, Yuan Z H, Sun G Y, Cong J. FPGA-based accelerator for long short-term memory recurrent neural networks. In Proc. the 22nd Asia and South Pacific Design Automation Conference, January 2017, pp.629-634.","DOI":"10.1109\/ASPDAC.2017.7858394"},{"key":"9686_CR11","unstructured":"Zhou Y M, Jiang J F. An FPGA-based accelerator implementation for deep convolutional neural networks. In Proc. the 4th International Conference on Computer Science Network Technology, December 2016, pp.829-832."},{"issue":"12","key":"9686_CR12","doi-asserted-by":"crossref","first-page":"2621","DOI":"10.1109\/TVLSI.2013.2294916","volume":"22","author":"D Neil","year":"2014","unstructured":"Neil D, Liu S C. Minitaur, an event-driven FPGA-based spiking network accelerator. IEEE Transactions on Very Large Scale Integration Systems, 2014, 22(12): 2621-2628.","journal-title":"IEEE Transactions on Very Large Scale Integration Systems"},{"issue":"3","key":"9686_CR13","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1109\/TBCAS.2017.2666883","volume":"11","author":"R Wang","year":"2017","unstructured":"Wang R, Thakur C S, Cohen G, Hamilton T J, Tapson J, van Schaik A. Neuromorphic hardware architecture using the neural engineering framework for pattern recognition. IEEE Trans. Biomed Circuits Syst., 2017, 11(3): 574-584.","journal-title":"IEEE Trans. Biomed Circuits Syst."},{"key":"9686_CR14","doi-asserted-by":"crossref","unstructured":"Glackin B, Mcginnity T M, Maguire L P, Wu Q X, Belatreche A. A novel approach for the implementation of large scale spiking neural networks on FPGA hardware. In Lecture Notes in Computer Science 3512, Cabestany J, Prieto A, Sandoral (eds.), Springer, 2005, pp.552-563.","DOI":"10.1007\/11494669_68"},{"key":"9686_CR15","doi-asserted-by":"crossref","unstructured":"Cheung K, Schultz S R, Luk W. A large-scale spiking neural network accelerator for FPGA systems. In Proc. the 22nd International Conference on Artificial Neural Networks, September 2012, pp.113-130.","DOI":"10.1007\/978-3-642-33269-2_15"},{"issue":"6","key":"9686_CR16","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1212\/WNL.18.6.612","volume":"18","author":"AL Benton","year":"1968","unstructured":"Benton A L. Foundations of physiological psychology. Neurology, 1968, 18(6): 609-612.","journal-title":"Neurology"},{"issue":"4","key":"9686_CR17","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1113\/jphysiol.1952.sp004716","volume":"116","author":"AL Hodgkin","year":"1952","unstructured":"Hodgkin A L, Huxley A F, Katz B. Measurement of current-voltage relations in the membrane of the giant axon of Loligo. J. Physiol., 1952, 116(4): 424-448.","journal-title":"J. Physiol."},{"issue":"6","key":"9686_CR18","doi-asserted-by":"crossref","first-page":"1569","DOI":"10.1109\/TNN.2003.820440","volume":"14","author":"EM Izhikevich","year":"2003","unstructured":"Izhikevich E M. Simple model of spiking neurons. IEEE Transactions on Neural Networks, 2003, 14(6): 1569-1572.","journal-title":"IEEE Transactions on Neural Networks"},{"issue":"5\/6","key":"9686_CR19","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1007\/s00422-007-0190-0","volume":"97","author":"N Brunel","year":"2007","unstructured":"Brunel N, van Rossum M C W. Lapicque\u2019s 1907 paper: From frogs to integrate-and-fire. Biological Cybernetics, 2007, 97(5\/6): 337-339.","journal-title":"Biological Cybernetics"},{"issue":"1","key":"9686_CR20","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1023\/A:1008916026143","volume":"10","author":"YH Liu","year":"2001","unstructured":"Liu Y H, Wang X J. Spike-frequency adaptation of a generalized leaky integrate-and-fire model neuron. Journal of Computational Neuroscience, 2001, 10(1): 25-45.","journal-title":"Journal of Computational Neuroscience"},{"issue":"5","key":"9686_CR21","doi-asserted-by":"crossref","first-page":"3637","DOI":"10.1152\/jn.00686.2005","volume":"94","author":"R Brette","year":"2005","unstructured":"Brette R, Gerstner W. Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. Journal of Neurophysiology, 2005, 94(5): 3637-3642.","journal-title":"Journal of Neurophysiology"},{"issue":"12","key":"9686_CR22","doi-asserted-by":"crossref","first-page":"2533","DOI":"10.1162\/0899766042321797","volume":"16","author":"L Paninski","year":"2014","unstructured":"Paninski L, Pillow J W, Simoncelli E P. Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model. Neural Computation, 2014, 16(12): 2533-2561.","journal-title":"Neural Computation"},{"issue":"4-6","key":"9686_CR23","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/j.neucom.2005.03.006","volume":"69","author":"K Tsumoto","year":"2006","unstructured":"Tsumoto K, Kitajima H, Yoshinaga T, Aihara K, Kawakami H. Bifurcations in Morris-Lecar neuron model. Neurocomputing, 2006, 69(4-6): 293-316.","journal-title":"Neurocomputing"},{"issue":"7","key":"9686_CR24","doi-asserted-by":"crossref","first-page":"956","DOI":"10.1109\/4.92015","volume":"26","author":"B Linares-Barranco","year":"1991","unstructured":"Linares-Barranco B, Sanchez-Sinencio E, Rodriguez-Vazquez A, Huertas J L. A CMOS implementation of the Fitzhugh-Nagumo neuron model. IEEE Journal of Solid-State Circuits, 1991, 26(7): 956-965.","journal-title":"IEEE Journal of Solid-State Circuits"},{"issue":"4","key":"9686_CR25","doi-asserted-by":"crossref","first-page":"1157","DOI":"10.1016\/j.asoc.2006.01.003","volume":"7","author":"RN Yadav","year":"2007","unstructured":"Yadav R N, Kalra P K, John J. Time series prediction with single multiplicative neuron model. Applied Soft Computing, 2007, 7(4): 1157-1163.","journal-title":"Applied Soft Computing"},{"issue":"1","key":"9686_CR26","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.neucom.2006.11.029","volume":"71","author":"LP Maguire","year":"2007","unstructured":"Maguire L P, Mcginnity T M, Glackin B, Ghani A, Belatreche A, Harkin J. Challenges for large-scale implementations of spiking neural networks on FPGAs. Neurocomputing, 2007, 71(1): 13-29.","journal-title":"Neurocomputing"},{"key":"9686_CR27","doi-asserted-by":"crossref","unstructured":"Gerstner W, Kistler W. Spiking Neuron Models: Single Neurons, Populations, Plasticity (1st edition). Cambridge University Press, 2002.","DOI":"10.1017\/CBO9780511815706"},{"key":"9686_CR28","doi-asserted-by":"crossref","unstructured":"Gerstner W. Spiking neuron models. In Encyclopedia of Neuroscience, Squire L R (ed.), Academic Press, 2009, pp.277-280.","DOI":"10.1016\/B978-008045046-9.01405-4"},{"issue":"7","key":"9686_CR29","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1109\/MC.1987.1663629","volume":"20","author":"DP Lopresti","year":"1987","unstructured":"Lopresti D P. P-NAC: A systolic array for comparing nucleic acid sequences. Computer, 1987, 20(7): 98-99.","journal-title":"Computer"},{"key":"9686_CR30","unstructured":"Samajdar A, Zhu Y, Whatmough P, Mattina M, Krishna T. SCALE-Sim: Systolic CNN accelerator simulator. Distributed, Parallel, and Cluster Computing, 2018."},{"key":"9686_CR31","unstructured":"Jouppi N P, Young C, Patil N et al. In-datacenter performance analysis of a tensor processing unit. In Proc. International Symposium on Computer Architecture, May 2017."},{"key":"9686_CR32","unstructured":"Simonyan K, Zisserman A. Very deep convolutional networks for large-scale image recognition. In Proc. the 3rd International Conference on Learning Representations, May 2015, Article No. 4."},{"key":"9686_CR33","doi-asserted-by":"crossref","unstructured":"Shen J C, Ma D, Gu Z H, Zhang M, Zhu X L, Xu X Q, Xu Q, Shen Y J, Pan G. Darwin: A neuromorphic hardware co-processor based on spiking neural networks. SCIENCE CHINA Information Sciences, 2016, 59(2): Article No. 023401.","DOI":"10.1007\/s11432-015-5511-7"},{"key":"9686_CR34","doi-asserted-by":"crossref","unstructured":"Kousanakis E, Dollas A, Sotiriades E et al. An architecture for the acceleration of a hybrid leaky integrate and fire SNN on the convey HC-2ex FPGA-based processor. In Proc. the 25th IEEE International Symposium on Field-programmable Custom Computing Machines, April 2017, pp.56-63.","DOI":"10.1109\/FCCM.2017.51"},{"key":"9686_CR35","unstructured":"Fang H, Shrestha A, Ma D et al. Scalable NoC-based neuromorphic hardware learning and inference. arXiv:1810.09233, 2018. https:\/\/arxiv.org\/pdf\/1810.0923-3v1.pdf, Dec. 2019."},{"key":"9686_CR36","doi-asserted-by":"crossref","unstructured":"Cheung K, Schultz S R, Luk W. NeuroFlow: A general purpose spiking neural network simulation platform using customizable processors. Frontiers in Neuroscience, 2015, 9: Article No. 516.","DOI":"10.3389\/fnins.2015.00516"},{"issue":"3","key":"9686_CR37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3007787.3001138","volume":"44","author":"J Albericio","year":"2016","unstructured":"Albericio J, Judd P, Hetherington T et al. Cnvlutin: Ineffectual-neuron-free deep neural network computing. ACM SIGARCH Computer Architecture News, 2016, 44(3): 1-13.","journal-title":"ACM SIGARCH Computer Architecture News"},{"issue":"1","key":"9686_CR38","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/LES.2019.2919244","volume":"12","author":"Shasha Guo","year":"2020","unstructured":"Guo S, Wang L, Chen B, Dou Q. An overhead-free max-pooling method for SNN. IEEE Embedded Systems Letters. https:\/\/doi.org\/10.1109\/LES.2019.2919244.","journal-title":"IEEE Embedded Systems Letters"}],"container-title":["Journal of Computer Science and Technology"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11390-020-9686-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11390-020-9686-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11390-020-9686-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,27]],"date-time":"2021-03-27T00:45:54Z","timestamp":1616805954000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11390-020-9686-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3]]},"references-count":38,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2020,3]]}},"alternative-id":["9686"],"URL":"https:\/\/doi.org\/10.1007\/s11390-020-9686-z","relation":{},"ISSN":["1000-9000","1860-4749"],"issn-type":[{"value":"1000-9000","type":"print"},{"value":"1860-4749","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,3]]},"assertion":[{"value":"1 May 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 February 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 March 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}