Computer Science ›› 2021, Vol. 48 ›› Issue (4): 205-212.doi: 10.11896/jsjkx.200600089
• Computer Graphics & Multimedia • Previous Articles Next Articles
QI Yan-rong1, ZHOU Xia-bing2, LI Bin1, ZHOU Qing-lei1
CLC Number:
[1]ZHOU F Y,JIN L F,DONG J.A review of convolutional neural network research[J].Journal of Computer Science,2017,40(6):1229-1251. [2]WU Y X,LIANG K,LIU Y,et al.Progress and Trend of DeepLearning FPGA Accelerator[J].Chinese Journal of Computers,2019,42(11):2461-2480. [3]AYDONAT U,O'CONNELL S,CAPALIJA D,et al.An opencl deep learning accelerator on arria 10[J].arXiv:1701.03534v1,2017. [4]QIU J,WANG J,YAO S,et al.Going deeper with embedded FPGA platform for convolutional neural network[C]//Acm/Sigda International Symposium on Field-programmable Gate Arrays.2016:26-35. [5]WANG C,GONG L,YU Q,et al.DLAU:A Scalable DeepLearning Accelerator Unit on FPGA[J].IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems,2017,36(3):513-517. [6]WANG D,XU K,JIANG D.PipeCNN:An OpenCL-based open-source FPGA accelerator for convolution neural networks[C]//2017 International Conference on Field Programmable Techno-logy(ICFPT).Melbourne,VIC,2017:279-282. [7]WANG D,AN J J,XU K.PipeCNN:An OpenCL-Based FPGA Accelerator for Large-Scale Convolution Neuron Networks[J].arXiv:1611.02450v1,2016. [8]ABDELOUAHAB K,PELCAT M,SÉROT J,et al.Tactics to Directly Map CNN Graphs on Embedded FPGAs[J].IEEE Embedded Systems Letters,2017,9(4):113-116. [9]WEI X C.Automated systolic array architecture synthesis forhigh throughput CNN inference on FPGAs[C]//2017 54th ACM/EDAC/IEEE Design Automation Conference(DAC).Austin,TX,2017:1-6. [10]WANG Y,ZHOU H Y,FENG H,et al.Network traffic classification method based on deep convolutional neural network [J].Journal of Communications,2018,39(1):14-23. [11]LU Y,CHEN Y,LI T,et al.Construction method of embedded FPGA convolutional neural network for edge computing[J].Computer Research and Development,2018,55(3):551-562. [12]ZHOU Y M,JIANG J F.An FPGA-based accelerator implementation for deep convolutional neural networks[C]//2015 4th International Conference on Computer Science and Network Technology(ICCSNT).Harbin,2015:829-832. [13]ZHANG C,LI P,SUN J,et al.Optimizing FPGA-based accele-rator design for deep convolutional neural networks[C]//Proc.ACM/SIGDA Int.Symp.Field Program.Gate Arrays.2015:161-170. [14]JIAN Q,ZHANG P Y,WANG X J.A configurable CNN co-accelerator FPGA implementation method[J].Acta Electronica Sinica,2019,47(7):1525-1531. [15]CHAKRADHAR S,SANKARADAS M,JAKKULA V,et al.A dynamically configurable coprocessor for convolutional neural networks[C]//Proc.ACM SIGARCH Comput.2010:247-257. [16]GOKHALE V,JIN J,DUNDAR A,et al.A 240 G-ops/s Mobile Coprocessor for Deep Neural Networks[C]//2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.Columbus,OH,2014:696-701. [17]SUDA N.Throughput-optimized OpenCL-based FPGA accelerator for large-scale convolutional neural networks[C]//Proc.ACM/SIGDA Int.Symp.Field Program.2016:16-25. [18]LU L,LIANG Y,XIAO Q,et al.Evaluating Fast Algorithms for Convolutional Neural Networks on FPGAs[C]//2017 IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines(FCCM).Napa,CA,2017:101-108. [19]HAN X,ZHOU D,WANG S,et al.CNN-MERP:An FPGA-based memory-efficient reconfigurable processor for forward and backward propagation of convolutional neural networks[C]//2016 IEEE 34th International Conference on Computer Design(ICCD).Scottsdale,AZ,2016:320-327. |
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