[1]丁科,谭营.GPU通用计算及其在计算智能领域的应用[J].智能系统学报,2015,10(1):1-11.[doi:10.3969/j.issn.1673-4785.201403072]
 DING Ke,TAN Ying.A review on general purpose computing on GPUs and its applications in computational intelligence[J].CAAI Transactions on Intelligent Systems,2015,10(1):1-11.[doi:10.3969/j.issn.1673-4785.201403072]
点击复制

GPU通用计算及其在计算智能领域的应用

参考文献/References:
[1] OWENS J D, LUEBKE D, GOVINDARAJU N, et al. A survey of general-purpose computation on graphics hardware[J]. Computer Graphics Forum, 2007, 26(1): 80-113.
[2] OWENS J D, LUEBKE D, GOVINDARAJU N, et al. GPU computing[J]. Proceedings of the IEEE, 2008, 96(5): 879-899.
[3] SUTTER H. The free lunch is over: a fundamental turn toward concurrency in software[J]. Dr. Dobb’s Journal, 2005, 30(3): 202-210.
[4] ROSS P E. Why CPU frequency stalled[J]. Spectrum, 2008, 45(4): 72-78.
[5] BORKAR S. Getting gigascale chips: challenges and opportunities in continuing Moore’s Law[J]. Queue, 2003, 1(7): 26-33.
[6] NVIDIA. CUDA C programming guide v6.5[R]. Santa Clara, CA, USA: NVIDIA Corporation, 2014.
[7] JARARWEH Y, JARRAH M, BOUSSELHAM A, et al. GPU-based personal supercomputing[C]//2013 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies. Amman, 2013: 1-5.
[8] KAPASI U J, RIXNER S, DALLY W J, et al. Programmable stream processors[J]. Computer, 2003, 36(8): 54-62.
[9] BUCK I, FOLEY T, HORN D, et al. Brook for GPUs: stream computing on graphics hardware[J]. ACM Transactions on Graphics, 2004, 23(3): 777-786.
[10] Microsoft. C++ accelerated massive parallelism[Z]. Redmond, WA, USA: Microsoft, 2013.
[11] NVIDIA. CUDA C best practices guide version 4.1[R]. Santa Clara, CA, USA: NVIDIA Corporation, 2012.
[12] NVIDIA. GPU-Accelerated Libraries.[OL/EB].[2015-01-05]. https://developer.nvidia.com/gpu-accelerated-libraries.
[13] JIA Y, SHELHAMER E, DONAHUE J, et al. Caffe: convolutional architecture for fast feature embedding[C]//Proceedings of the ACM International Conference on Multimedia,[s.l.], 2014: 675-678.
[14] GASTER B, HOWES L, KAELI D R,等. OpenCL异构计算[M]. 北京: 清华大学出版社, 2012: 10-35.
[15] KIRK D B, HWU W W. Programming massively parallel processors: a Hands-on approach[M]. Beijing: Tsinghua University Press, 2010: 205-220.
[16] MUNSHI A, GASTER B, MATTSON T G, et al. OpenCL Programming Guide[M]. Boston: Addison_Wesley Professional, 2011: 63-68.
[17] AMD上海研发中心. 跨平台的多核与从核编程讲义——OpenCL的方式[M]. 上海: AMD, 2010: 1-154.
[18] FARBER R. 高性能 CUDA应用设计与开发[M]. 北京:机械工业出版社, 2013: 1-49.
[19] ZEILER M, FERGUS R. Visualizing and understanding convolutional networks[C]//Proceedings of the 13th European Conference on Computer Vision. Zurich, Switzerland, 2014: 818-833.
[20] HINTON G, OSINDERO S, WELLING M, et al. Unsupervised discovery of nonlinear structure using contrastive backpropagation[J]. Nature, 2006, 30(4): 725-731.
[21] KRIZHEVSKY A, SUTSKEVER I, HINTON G. Imagenet classification with deep convolutional neural networks[C]//Advances in Neural Information Processing Systems 25. Reno, Nevada, USA, 2012: 1106-1114.
[22] COATES A, HUVAL B, WANG T, et al. Deep learning with COTS HPC systems[C]//Proceedings of the 30th International Conference on Machine Learning. Atlanta, USA, 2013: 1337-1345.
[23] ZHOU Y, TAN Y. GPU-based parallel particle swarm optimization[C]//IEEE Congress on Evolutionary Computation. Trondheim, Norway, 2009: 1493-1500.
[24] ZHOU Y, TAN Y. Particle swarm optimization with triggered mutation and its implementation based on GPU[C]//GECCO’10: Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation. Portland, Oregon, USA, 2010: 1-8.
[25] ZHOU Y, TAN Y. GPU-based parallel multi-objective particle swarm optimization[J]. International Journal of Artificial Intelligence, 2011, 7(A11): 125-141.
[26] DING K, TAN Y. A GPU-based parallel fireworks algorithm for optimization[C]//GECCO’13: Proceedings of the Fifteenth Annual Conference on Genetic and Evolutionary Computation Conference. Amsterdam, the Netherlands, 2013: 9-16.
[27] TAN Y, ZHU Y. Fireworks algorithm for optimization[C]//First International Conference of Swarm Intelligence. Beijing, China, 2010: 355-364.
[28] RYMUT B, KWOLEK B. GPU-supported object tracking using adaptive appearance models and particle swarm optimization[C]//International Conference on Computer Vision and Graphics, Warsaw, Poland, 2010: 227-234.
[29] MUSSI L, IVEKOVIC S, CAGNONI S. Markerless articulated human body tracking from multi-view video with GPU-PSO[C]//9th International Conference on Environmental Systems. York, UK, 2010: 97-108.
[30] NOBILE M S, BESOZZI D, CAZZANIGA P, et al. A GPU-based multi-swarm PSO method for parameter estimation in stochastic biological systems exploiting discrete-time target series[C]//10th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Computational Biology. Málaga, Spain, 2012, 7246: 74-85.
[31] MAGHAZEH A, BORDOLOI UD, ELES P, et al. General purpose computing on low-power embedded GPUs: has it come of age[R]. Linkping University Electronic Press, 2013.
[32] HALLMANS D, SANDSTROM K, LINDGREN M, et al. GPGPU for industrial control systems[C]//2013 IEEE 18th Conference on Emerging Technologies Factory Automation. Cagliari, Italy, 2013: 1-4.
相似文献/References:
[1]丁永生.计算智能的新框架:生物网络结构[J].智能系统学报,2007,2(2):26.
 DING Yong-sheng.A new scheme for computational intelligence: bio-network architecture[J].CAAI Transactions on Intelligent Systems,2007,2(1):26.
[2]康 琦,汪 镭,刘小莉,等.基于群体智能框架理念的遗传算法总体模式描述[J].智能系统学报,2007,2(5):42.
 KANG Qi,WANG Lei,LIU Xiao-li,et al.General mode description genetic algorithms based on a framework of swarm intelligence[J].CAAI Transactions on Intelligent Systems,2007,2(1):42.
[3]杨东升,康 琦,刘 波,等.面向生产系统的残次品主次成因的群体智能分析[J].智能系统学报,2009,4(6):502.[doi:10.3969/j.issn.1673-4785.2009.06.006]
 YANG Dong-sheng,KANG Qi,LIU Bo,et al.Swarm intelligence analysis of primary and secondary causes of defective products for manufacturing system[J].CAAI Transactions on Intelligent Systems,2009,4(1):502.[doi:10.3969/j.issn.1673-4785.2009.06.006]
[4]夏琳琳,张健沛,初妍.计算智能在移动机器人路径规划中的应用综述[J].智能系统学报,2011,6(2):160.
 XIA Linlin,ZHANG Jianpei,CHU Yan.An application survey on computational intelligence for path planning of mobile robots[J].CAAI Transactions on Intelligent Systems,2011,6(1):160.
[5]陈杰,沈艳霞,陆欣.基于信息反馈和改进适应度评价的人工蜂群算法[J].智能系统学报,2016,11(2):172.[doi:10.11992/tis.201506024]
 CHEN Jie,SHEN Yanxia,LU Xin.Artificial bee colony algorithm based on information feedback and an improved fitness value evaluation[J].CAAI Transactions on Intelligent Systems,2016,11(1):172.[doi:10.11992/tis.201506024]
[6]秦全德,程适,李丽,等.人工蜂群算法研究综述[J].智能系统学报,2014,9(2):127.[doi:10.3969/j.issn.1673-4785.201309064]
 QIN Quande,CHENG Shi,LI Li,et al.Artificial bee colony algorithm: a survey[J].CAAI Transactions on Intelligent Systems,2014,9(1):127.[doi:10.3969/j.issn.1673-4785.201309064]
[7]谭营,郑少秋.烟花算法研究进展[J].智能系统学报,2014,9(5):515.[doi:10.3969/j.issn.1673-4785.201409010]
 TAN Ying,ZHENG Shaoqiu.Recent advances in fireworks algorithm[J].CAAI Transactions on Intelligent Systems,2014,9(1):515.[doi:10.3969/j.issn.1673-4785.201409010]
[8]顾大强,郑文钢.多移动机器人协同搬运技术综述[J].智能系统学报,2019,14(1):20.[doi:10.11992/tis.201801038]
 GU Daqiang,ZHENG Wengang.Technologies for cooperative transportation by multiple mobile robots[J].CAAI Transactions on Intelligent Systems,2019,14(1):20.[doi:10.11992/tis.201801038]
[9]李景灿,丁世飞.基于人工鱼群算法的孪生支持向量机[J].智能系统学报,2019,14(6):1121.[doi:10.11992/tis.201905025]
 LI Jingcan,DING Shifei.Twin support vector machine based on artificial fish swarm algorithm[J].CAAI Transactions on Intelligent Systems,2019,14(1):1121.[doi:10.11992/tis.201905025]
[10]邱华鑫,段海滨,范彦铭,等.鸽群交互模式切换模型及其同步性分析[J].智能系统学报,2020,15(2):334.[doi:10.11992/tis.201904052]
 QIU Huaxin,DUAN Haibin,FAN Yanming,et al.Pigeon flock interaction pattern switching model and its synchronization analysis[J].CAAI Transactions on Intelligent Systems,2020,15(1):334.[doi:10.11992/tis.201904052]

备注/Memo

收稿日期:2014-12-18;改回日期:。
基金项目:国家自然科学基金资助项目(61375119,61170057,60875080).
作者简介:丁科,男,1989年生,博士研究生,主要研究方向为群体智能、GPU通用计算、并行编程和机器学习;谭营,男,1964年生,教授,博士生导师,主要研究方向为计算智能、群体智能、机器学习、人工免疫系统、智能信息处理及信息安全应用。担任IJCIPT主编,IJSIR副主编,IEEE Trans on Cybernetics副主编等,IEEE Senior Member, IEEE CIS-ETTC委员,ICSI系列会议大会主席。主持国家“863”计划、国家自然科学基金、国际合作交流等科研项目30余项。获得2009年度国家自然科学二等奖。获国家发明专利授权3项,发表学术论文260余篇,出版专著5部。
通讯作者:谭营.E-mail:ytan@pku.edu.cn.

更新日期/Last Update: 2015-06-16
Copyright @ 《 智能系统学报》 编辑部
地址:(150001)黑龙江省哈尔滨市南岗区南通大街145-1号楼 电话:0451- 82534001、82518134