盲优化软硬件划分技术研究
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摘要
在软硬件结合的嵌入式系统设计中，往往采用软硬件协同设计方法以缩短系统的研发周期，同时降低系统在成本、功耗等多方面的需求，而软硬件划分是软硬件协同设计中的重点和难点。现有的静态软硬件划分算法存在通用性差、对参数设置敏感、计算复杂等问题，而对动态软硬件划分的研究成果较少。本文以盲优化为主线对软硬件划分中划分与调度技术进行了深入研究，完成了以下工作：
分析并指出了非盲优化软硬件划分中一维搜索算法存在的局限性，提出了基于贪婪规则的描述方法，该方法及相关定理的引入明确了一维搜索可以找到最优解的前提条件，保证了原理和算法的一致性。
将人工鱼群算法引入到软硬件划分领域，从而提出一种新的软硬件划分盲优化方法。针对其应用于离散型问题时普遍存在的最优解出现概率低、收敛速度慢等问题，提出了基于随机步长和邻域搜索的改进方法。实验结果表明，改进后算法在寻优能力和收敛速度上优于原始算法，可更高效地完成软硬件划分任务。
针对大规模系统的软硬件划分问题，提出了基于混合蛙跳算法的软硬件划分盲优化方法，并针对其存在的全局寻优能力差、收敛效率低等问题，提出了基于同优状态复位和双层自适应邻域搜索的改进方法。实验结果表明，在平均执行时间小于原算法的前提下，改进后算法的最优解等于或优于原算法，且最优解出现的次数等于或高于原算法。因此，改进后算法具有更强的全局寻优能力和更高的收敛效率。
针对盲优化软硬件划分中的任务调度问题，提出了面向任务调度长度的METF算法和面向通信存储能力的MDF、MRF算法，并通过随机DAG图调度实验证明了以上三种算法的有效性。
针对盲优化动态软硬件划分中的任务预测问题，提出了基于有序周期基的任务预测算法。对所选任务序列的预测实验表明，该算法具有一定的任务预测能力，可完成动态软硬件划分系统的预测任务。
The method of hardware software co-design is always used in embedded systemdesign to shorten the development cycle of the system, while reducing system cost,power consumption, and many other requirements. And the emphasis and difficulty ofhardware software co-design is HW/SW partitioning. The existing algorithms forstatic HW/SW partitioning have sensitive parameter settings, high computationalcomplexity or other problems, while there is less study for dynamic HW/SWpartitioning. So, in the paper, the partitioning and scheduling technologies in HW/SWpartitioning are in-depth studied with the main clue of blind optimization, and thefollowing work is completed.
The limitation of1DS algorithm in HW/SW partitioning is analyzed and pointedout, and then a description method based on greedy rule is proposed. The introducedmethod and related theorem make clear the precondition of finding optimumsolutions, and ensure the consistency of the theory and algorithm.
The AFSA is introduced to HW/SW partitioning and a novel blind optimizationmethod for HW/SW partitioning is proposed. When AFSA is applied to solve discreteproblems, the optimum solution occurrence probability and the convergence speed arelow. So the improved methods based on random step and neighborhood searching areproposed. Experimental results show that the improved AFSA can achieve results insearch ability and convergence speed superior to original algorithm. Thus theimproved AFSA can execute HW/SW partitioning much more efficiently.
The blind optimization method based on SFLA is introduced to HW/SWpartitioning for large-scale systems, and the improved methods based on same stateresetting and double-layer adaptive neighborhood searching are adopted to solve theproblems of poor global searching ability and low convergence efficiency.Experimental results show that, within a shorter run time, the optimum solution ofimproved SFLA is equal to or better than that of the original algorithm, and theoptimum solution occurrence probability is equal to or higher than that of the originalalgorithm. Thus the improved SFLA has better global searching ability and higherconvergence efficiency.
Aiming at the task scheduling problem of blind-optimization-based HW/SWpartitioning, the METF algorithm oriented to scheduling length and the MDF, MRFalgorithm oriented to communication storage ability are proposed. Finally, theefficiency of the three algorithms is proved through scheduling experiments withrandom DAGs.
Aiming at the task prediction problem of blind-optimization-based dynamicHW/SW partitioning, a task prediction algorithm based on ordered periodic base isproposed. The experiments of task scheduling prediction for selected task sequencesshow that the algorithm has the ability of task prediction and can complete predictiontasks for dynamic HW/SW partitioning.
分析并指出了非盲优化软硬件划分中一维搜索算法存在的局限性，提出了基于贪婪规则的描述方法，该方法及相关定理的引入明确了一维搜索可以找到最优解的前提条件，保证了原理和算法的一致性。
将人工鱼群算法引入到软硬件划分领域，从而提出一种新的软硬件划分盲优化方法。针对其应用于离散型问题时普遍存在的最优解出现概率低、收敛速度慢等问题，提出了基于随机步长和邻域搜索的改进方法。实验结果表明，改进后算法在寻优能力和收敛速度上优于原始算法，可更高效地完成软硬件划分任务。
针对大规模系统的软硬件划分问题，提出了基于混合蛙跳算法的软硬件划分盲优化方法，并针对其存在的全局寻优能力差、收敛效率低等问题，提出了基于同优状态复位和双层自适应邻域搜索的改进方法。实验结果表明，在平均执行时间小于原算法的前提下，改进后算法的最优解等于或优于原算法，且最优解出现的次数等于或高于原算法。因此，改进后算法具有更强的全局寻优能力和更高的收敛效率。
针对盲优化软硬件划分中的任务调度问题，提出了面向任务调度长度的METF算法和面向通信存储能力的MDF、MRF算法，并通过随机DAG图调度实验证明了以上三种算法的有效性。
针对盲优化动态软硬件划分中的任务预测问题，提出了基于有序周期基的任务预测算法。对所选任务序列的预测实验表明，该算法具有一定的任务预测能力，可完成动态软硬件划分系统的预测任务。
The method of hardware software co-design is always used in embedded systemdesign to shorten the development cycle of the system, while reducing system cost,power consumption, and many other requirements. And the emphasis and difficulty ofhardware software co-design is HW/SW partitioning. The existing algorithms forstatic HW/SW partitioning have sensitive parameter settings, high computationalcomplexity or other problems, while there is less study for dynamic HW/SWpartitioning. So, in the paper, the partitioning and scheduling technologies in HW/SWpartitioning are in-depth studied with the main clue of blind optimization, and thefollowing work is completed.
The limitation of1DS algorithm in HW/SW partitioning is analyzed and pointedout, and then a description method based on greedy rule is proposed. The introducedmethod and related theorem make clear the precondition of finding optimumsolutions, and ensure the consistency of the theory and algorithm.
The AFSA is introduced to HW/SW partitioning and a novel blind optimizationmethod for HW/SW partitioning is proposed. When AFSA is applied to solve discreteproblems, the optimum solution occurrence probability and the convergence speed arelow. So the improved methods based on random step and neighborhood searching areproposed. Experimental results show that the improved AFSA can achieve results insearch ability and convergence speed superior to original algorithm. Thus theimproved AFSA can execute HW/SW partitioning much more efficiently.
The blind optimization method based on SFLA is introduced to HW/SWpartitioning for large-scale systems, and the improved methods based on same stateresetting and double-layer adaptive neighborhood searching are adopted to solve theproblems of poor global searching ability and low convergence efficiency.Experimental results show that, within a shorter run time, the optimum solution ofimproved SFLA is equal to or better than that of the original algorithm, and theoptimum solution occurrence probability is equal to or higher than that of the originalalgorithm. Thus the improved SFLA has better global searching ability and higherconvergence efficiency.
Aiming at the task scheduling problem of blind-optimization-based HW/SWpartitioning, the METF algorithm oriented to scheduling length and the MDF, MRFalgorithm oriented to communication storage ability are proposed. Finally, theefficiency of the three algorithms is proved through scheduling experiments withrandom DAGs.
Aiming at the task prediction problem of blind-optimization-based dynamicHW/SW partitioning, a task prediction algorithm based on ordered periodic base isproposed. The experiments of task scheduling prediction for selected task sequencesshow that the algorithm has the ability of task prediction and can complete predictiontasks for dynamic HW/SW partitioning.
引文
[1]邓中亮，段大高，崔岩松，嵌入式系统设计，北京：北京邮电大学出版社，2008，1
[2] Ye H, Wu J, Computing models and algorithms for complex co-design systems,Journal of the University of Electronic Science and Technology of China,2011,40(3):333-345
[3] Abdelhalim M B, Habib S E D, An integrated high-level hardware/softwarepartitioning methodology, Design Automation for Embedded Systems,2011,15(1):19-50
[4]于苏东，刘雷波，尹首一等，嵌入式粗颗粒度可重构处理器的软硬件协同设计流程，电子学报，2009，37（5）：1136-1140
[5] Knudsen P V, Madsen J, PACE: A dynamic programming algorithm forhardware/software partitioning,4th International Workshop on Hardware/SoftwareCo-Design, Codes/CASHE'96, Pittsburgh, PA, USA: IEEE,1996,85-92
[6] Shrivastava A, Kumar M, Kapoor S, et al., Optimal hardware/software partitioningfor concurrent specification using dynamic programming, The13th InternationalConference on VLSI Design: Wireless and Digital Imaging in the Millennium,Calcutta, India: IEEE,2000,110-113
[7] Chang J, Pedram M, Codex-dp: co-design of communicating systems usingdynamic programming, IEEE Transactions on Computer-Aided Design of IntegratedCircuits and Systems,2000,19(7):732-744
[8] Wu J, Srikanthan T, Low-complex dynamic programming algorithm forhardware/software partitioning, Information Processing Letters,2006,98(2):41-46
[9] Niemann R, Marwedel P, Algorithm for hardware/software partitioning usingmixed integer linear programming, Design Automation for Embedded Systems,1997,2(2):165-193
[10] Kuang S, Chen C, Liao R, Partitioning and pipelined scheduling of embeddedsystem using integer linear programming,11th International Conference on Paralleland Distributed Systems Workshops, ICPADS2005, Fukuoka, Japan: Institute ofElectrical and Electronics Engineers Computer Society,2005,37-41
[11] Binh N N, Imai M, Shiomi A, et al., Hardware/software partitioning algorithmfor designing pipelined ASIPs with least gate counts,33rd Annual Design AutomationConference, Las Vegas, NV, USA: IEEE,1996,527-532
[12] Alomary A Y, Hardware/software codesign partitioner for ASIP design,3rdIEEE International Conference on Electronics, Circuits, and Systems, ICECS1996,Rodos, Greece: IEEE,1996,251-254
[13] Chatha K S, Vemuri R, Hardware-software partitioning and pipelined schedulingof transformative applications, IEEE Transactions on Very Large Scale Integration(VLSI) Systems,2002,10(3):193-208
[14] Jigang W, Thambipillai S, A branch-and-bound algorithm for hardware/softwarepartitioning,4th IEEE International Symposium on Signal processing and InformationTechnology, ISSPIT2004, Rome, Italy: Institute of Electrical and ElectronicsEngineers Inc.,2004,526-529
[15]盛蓝平，林涛，采用启发式分支定界的软硬件划分，计算机辅助设计与图形学学报，2005，17（3）：414-417
[16] Mann Z A, Orban A, Arato P, Finding optimal hardware/software partitions,Formal Methods in System Design,2007,31(3):241-263
[17] Jigang W, Chang B, Srikanthan T, A hybrid branch-and-bound strategy forhardware/software partitioning,8th IEEE/ACIS International Conference onComputer and Information Science, ICIS2009, Shanghai, China: IEEE ComputerSociety,2009,641-644
[18] Zhang Y, Kandemir M, A hardware-software codesign strategy for loop intensiveapplications,2009IEEE7th Symposium on Application Specific Processors, SASP2009, San Francisco, CA, United states: IEEE Computer Society,2009,107-113
[19] Wu J, Srikanthan T, Guang C, Algorithmic aspects of hardware/softwarepartitioning:1D search algorithms, IEEE Transactions on Computers,2010,59(4):532-544
[20] Saha D, Mitra R S, Basu A, Hardware software partitioning using geneticalgorithm, the199710th International Conference on VLSI Design, Hyderabad, India:IEEE,1997,155-160
[21] Harkin J, Mcginnity T M, Maguire L P, Genetic algorithm drivenhardware-software partitioning for dynamically reconfigurable embedded systems,Microprocessors and Microsystems,2001,25(5):263-274
[22] Farahani A F, Kamal M, Salmani-Jelodar M, Parallel-genetic-algorithm-basedHW/SW partitioning, International Symposium on Parallel Computing in ElectricalEngineering, PARELEC2006, Bialystok, Poland: IEEE Computer Society,2006,337-342
[23] Mudry P, Zufferey G, Tempesti G, A dynamically constrained genetic algorithmfor hardware-software partitioning,8th Annual Genetic and EvolutionaryComputation Conference, Seattle, WA, United states: Association for ComputingMachinery,2006,769-775
[24] Arunachalam V, Sapra S, Chaitanya N S K, et al., Hardware/softwarepartitioning algorithm for embedded systems with repeated functionalities,2008IEEERegion10Conference, TENCON2008, Hyderabad, India: Institute of Electrical andElectronics Engineers Inc.,2008,1-6
[25] Lee T, Fan Y, Cheng Y, et al., Hardware-software partitioning for embeddedmultiprocessor FPGA systems, International Journal of Innovative Computing,Information and Control,2009,5(10):3071-3083
[26]罗胜钦，马萧萧，陆忆，基于改进的NSGA遗传算法的SOC软硬件划分方法，电子学报，2009，37（11）：2595-2599
[27] Zheng S, Zhang Y, He T, The application of genetic algorithm in embeddedsystem hardware-software partitioning,2009International Conference on ElectronicComputer Technology, ICECT2009, Macau, China: Inst. of Elec. and Elec. Eng.Computer Society,2009,219-222
[28] Li L, Hongjun H, Qiang D, et al., Hardware/software partitioning forheterogeneous multicore SoC using genetic algorithm,2nd International Conferenceon Intelligent System Design and Engineering Application, ISDEA2012, Sanya,Hainan, China: IEEE Computer Society,2012,1267-1270
[29] Lin T, Sait S M, Cyre W R, Buffer size driven partitioning for HW/SW co-design,the1998IEEE International Conference on Computer Design, Austin, TX, USA:IEEE,1998,596-601
[30] Purnaprajna M, Reformat M, Pedrycz W, Genetic algorithms inhardware-software partitioning, the International Conference on Engineering ofReconfigurable Systems and Algorithms, ERSA'04, Las Vegas, NV, United states:CSREA Press,2004,123-129
[31] Purnaprajna M, Reformat M, Pedrycz W, Genetic algorithms forhardware-software partitioning and optimal resource allocation, Journal of SystemsArchitecture,2007,53(7):339-354
[32] Jagadeeswari M, Bhuvaneswari M C, Efficient multi-objective genetic algorithmfor hardware-software partitioning in embedded system design: ENGA, InternationalJournal of Computer Applications in Technology,2009,36(3-4):181-190
[33] Fu Y, Liu X, Guo P, A multi-objective optimization genetic algorithm for SOPChardware-software partitioning,2011International Conference on AdvancedMaterials and Engineering Materials, ICAMEM2011, Shenyang, Liaoning, China:Trans Tech Publications,2012,1142-1148
[34] Chehida K B, Auguin M, HW/SW partitioning approach for reconfigurablesystem design,2002International Conference on Compilers, Architecture, andSynthesis for Embedded Systems, CASES '02, Grenoble, France: Association forComputing Machinery,2002,247-251
[35] Zou Y, Zhuang Z, Chen H, HW-SW partitioning based on genetic algorithm, the2004Congress on Evolutionary Computation, CEC2004, Portland, OR, United states:Institute of Electrical and Electronics Engineers Inc.,2004,628-633
[36] Dou S, Ding S, Zhang S, et al., GA-based algorithm for hardware/softwarepartitioning with resource contentions,2010IEEE International Conference onAdvanced Computer Control, ICACC2010, New Jersey, United States: IEEEComputer Society,2010,68-72
[37]郭晓东，刘积仁，一种基于模拟退火算法的硬件/软件分解方法，东北大学学报：自然科学版，2000，21（3）：233-236
[38] Eles P, Peng Z, Kuchcinski K, et al., System level hardware/software partitioningbased on simulated annealing and tabu search, Design Automation for EmbeddedSystems,1997,2(1):5-32
[39] Eles P, Peng Z, Kuchcinski K, et al., Hardware/software partitioning withiterative improvement heuristics,9th International Symposium on System Synthesis,ISSS'96, La Jolla, CA, USA: IEEE,1996,71-76
[40]彭艺频，凌明，杨军，性能受限系统的软硬件划分方法，东南大学学报：自然科学版，2004，34（6）：828-832
[41] Zebo P, Kuchcinski K, An algorithm for partitioning of application specificsystems,4th European Conference on Design Automation with the European Event inASIC Design, EDAC1993, Paris, Fr: Publ by IEEE,1993,316-321
[42] Abdelhalim M B, Salama A E, Habib S E D, Hardware software partitioningusing particle swarm optimization technique,6th IEEE International Workshop onSystem on Chip for Real Time Applications, IWSOC2006, Cairo, Egypt: Inst. of Elec.and Elec. Eng. Computer Society,2006,189-194
[43] Abdelhalim M B, Habib S E D, Modeling communication cost and hardwarealternatives in PSO based HW/SW partitioning,19th International Conference onMicroelectronics, ICM2007, Cairo, Egypt: Institute of Electrical and ElectronicsEngineers Inc.,2007,111-114
[44] Farmahini-Farahani A, Kamal M, Fakhraie S M, et al., HW/SW partitioningusing discrete particle swarm,17th Great Lakes Symposium on VLSI, GLSVLSI'07,Stresa-Lago Maggiore, Italy: Association for Computing Machinery,2007,359-364
[45] Bhattacharya A, Konar A, Das S, et al., Hardware software partitioning problemin embedded system design using particle swarm optimization algorithm,2ndInternational Conference on Complex, Intelligent and Software IntensiveSystems,CISIS2008, Barcelona, Spain: Inst. of Elec. and Elec. Eng. ComputerSociety,2008,171-176
[46] Qiaoling T, Xuecheng Z, Qiao Z, et al., The hardware/software partitioning inembedded system by improved particle swarm optimization algorithm, The5th IEEEInternational Symposium on Embedded Computing, SEC2008, Beijing, China: Inst.of Elec. and Elec. Eng. Computer Society,2008,43-46
[47] Yuan J, Peng M, Hardware/Software partitioning algorithm based on waveletmutation binary particle swarm optimization,2011IEEE3rd International Conferenceon Communication Software and Networks, ICCSN2011, Xi'an, China: IEEEComputer Society,2011,347-350
[48] Zhao H, Weng X W, Chen C, et al., Research on hardware/software partition offuture transfiguration aircraft store management system,201224th Chinese Controland Decision Conference, CCDC2012, Taiyuan, China: IEEE Computer Society,2012,483-487
[49] Ahmed U, Khan G N, Embedded system partitioning with flexible granularity byusing a variant of Tabu Search, Canadian Conference on Electrical and ComputerEngineering, CCECE2004, Niagara Falls, Canada: Institute of Electrical andElectronics Engineers Inc.,2004,2073-2076
[50] Pu G, Chong Z, Qiu Z, et al., A hybrid heuristic algorithm for HW-SWpartitioning within timed automata,10th International Conference onKnowledge-Based Intelligent Information and Engineering Systems, KES2006,Bournemouth, United kingdom: Springer Verlag,2006,459-466
[51] Pu G, Chong Z, Qiu Z, et al., Integrating timed automata into tabu algorithm forHW-SW partitioning,11th IEEE International Conference on Engineering ofComplex Computer Systems, ICECCS2006, Stanford, CA, United states: Institute ofElectrical and Electronics Engineers Inc.,2006,131-138
[52] Wu J, Srikanthan T, Lei T, Efficient heuristic algorithms for path-basedhardware/software partitioning, Mathematical and Computer Modelling,2010,51(7-8):974-984
[53] Wu J, Sun Q, Srikanthan T, Algorithmic aspects for multiple-choicehardware/software partitioning, Computers and Operations Research,2012,39(12):3281-3292
[54] Yu H, Fan X, Zhang S, et al., A guiding function based greedy partitioningalgorithm for dynamically reconfigurable systems,8th International Conference onSolid-State and Integrated Circuit Technology, ICSICT2006, Shanghai, China: Inst.of Elec. and Elec. Eng. Computer Society,2007,2009-2012
[55] Wang H, Zhang H, Improved HW/SW partitioning algorithm on efficient use ofhardware resource,2nd International Conference on Computer and AutomationEngineering, ICCAE2010, Singapore, Singapore: IEEE Computer Society,2010,682-685
[56] Li N, Fang Y, Software/hardware partition in multiple processors embeddedsystem, International Conference on Machine Learning and Cybernetics, ICMLC2005, Guangzhou, China: Institute of Electrical and Electronics Engineers ComputerSociety,2005,165-170
[57] Li S, Wang D, Li T, et al., Distributed collaborative partition method ofreconfigurable SoC using ant colony optimization,11th International Conference onComputer Supported Cooperative Work in Design, CSCWD2007, Melbourne, VIC,Australia: Inst. of Elec. and Elec. Eng. Computer Society,2007,133-138
[58] Wang D, Li S, Dou Y, Collaborative hardware/software partition ofcoarse-grained reconfigurable system using evolutionary ant colony optimization,2008Asia and South Pacific Design Automation Conference, ASP-DAC2008, Seoul,Korea, Republic of: Institute of Electrical and Electronics Engineers Inc.,2008,679-684
[59]张煜东，吴乐南，韦耿等，基于自适应蚁群算法的软硬件划分，控制与决策，2009，24（9）：1385-1389
[60] Ferrandi F, Pilato C, Sciuto D, et al., Mapping and scheduling of parallel Capplications with ant colony optimization onto heterogeneous reconfigurable MPSoCs,201015th Asia and South Pacific Design Automation Conference, ASP-DAC2010,Taipei, Taiwan: Institute of Electrical and Electronics Engineers Inc.,2010,799-804
[61] Liu Y, Li Q C, Liu J X, et al., Study on hardware software partitioning usingimmune algorithm and its convergence property,2009IEEE International Conferenceon Intelligent Computing and Intelligent Systems, ICIS2009, Shanghai, China: IEEEComputer Society,2009,4-8
[62]邢冀鹏，邹雪城，刘政林等，基于混沌优化算法的软硬件划分，华中科技大学学报：自然科学版，2006，34（11）：61-63
[63] Vahid F, Modifying min-cut for hardware and software functional partitioning,the19975th International Workshop on Hardware/Software Codesign,CODES/CASHE'97, Braunschweig, Ger: IEEE,1997,43-48
[64] Vahid F, Le T D, Extending the Kernighan/Lin heuristic for hardware andsoftware functional partitioning, Design Automation for Embedded Systems,1997,2(2):237-261
[65]郭兵，沈艳，王典辉等，一种基于离散Hopfield神经网络的SoC嵌入式操作系统软/硬件划分方法，四川大学学报：工程科学版，2006，38（5）：122-127
[66] Guo B, Shen Y, Hardware-software partitioning of embedded operating systemin the SoC using a discrete hopfield neural network approach, Chinese Journal ofElectronics,2007,16(1):13-17
[67] Guo B, Shen Y, Huang Y, et al., A novel discrete hopfield neural networkapproach for hardware-software partitioning of RTOS in the SoC, Embedded andUbiquitous Computing Workshops, EUC2006, Seoul, Korea, Republic of: SpringerVerlag,2006,888-897
[68] Li L, Song Y, Gao M, A new genetic simulated annealing algorithm forhardware-software partitioning,2nd International Conference on Information Scienceand Engineering, ICISE2010, Hangzhou, China: IEEE Computer Society,2010,1-4
[69]熊志辉，李恩昆，陈吉华，遗传算法与蚂蚁算法动态融合的软硬件划分，软件学报，2005，16（4）：503-512
[70] Zhao X, Li L, Gao M, Research on hardware-software partitioning method fordynamically reconfigurable embedded system,2012International Applied Mechanics,MechatronicsAutomation and System Simulation Meeting, AMMASS2012,Hangzhou, China: Trans Tech Publications,2012,606-610
[71]刘安，冯金富，梁晓龙等，基于遗传粒子群优化的嵌入式系统软硬件划分算法，计算机辅助设计与图形学学报，2010，22（6）：927-933
[72] Cui L, A novel approach to hardware/software partitioning for reconfigurableembedded systems, Journal of Computers (Finland),2012,7(10SPL.ISS.):2518-2525
[73] Wu Y, Zhang H, Yang H, Research on parallel HW/SW partitioning based onhybrid PSO algorithm,9th International Conference on Algorithms and Architecturesfor Parallel Processing, ICA3PP2009, Taipei, Taiwan: Springer Verlag,2009,449-459
[74] Eimuri T, Salehi S, Using DPSO and B&B algorithms for Hardware/Softwarepartitioning in co-design,2nd International Conference on Computer Research andDevelopment, ICCRD2010, Kuala Lumpur, Malaysia: IEEE Computer Society,2010,416-420
[75] Luo L, He H, Liao C, et al., Hardware/software partitioning for heterogeneousmulticore SOC using Particle Swarm Optimization and Immune Clone (PSO-IC)algorithm,2010IEEE International Conference on Information and Automation, ICIA2010, Harbin, Heilongjiang, China: IEEE Computer Society,2010,490-494
[76] Ma T, Yang J, Wang X, Low power hardware-software partitioning algorithm forheterogeneous distributed embedded systems, International Conference on Embeddedand Ubiquitous Computing, EUC2006, Seoul, Korea, Republic of: Springer Verlag,2006,702-711
[77] Ma T, Li Z, Yang J, A novel neural network search for energy-efficienthardware-software partitioning,2006International Conference on Machine Learningand Cybernetics, Dalian, China: Inst. of Elec. and Elec. Eng. Computer Society,2006,3053-3058
[78] Liu P, Wu J, Wang Y, Hybrid algorithms for hardware/software partitioning andscheduling on reconfigurable devices, Mathematical and Computer Modelling,2012:In Press
[79] Pan Z, Li W, Shao Q, et al., Hardware-software partitioning for the design ofsystem on chip by neural network optimization method,7th International Symposiumon Precision Engineering Measurements and Instrumentation, Lijiang, China: SPIE,2011
[80] Strachacki M, Speedup of branch and bound method for hardware/softwarepartitioning,20081st International Conference on Information Technology, IT2008,Gdansk, Poland: Inst. of Elec. and Elec. Eng. Computer Society,2008,1-4
[81] Huang Y, Kim Y, Applying hybrid neural fuzzy system to embedded systemhardware/software partitioning,3rd International Conference on IntelligentComputing, ICIC2007, Qingdao, China: Springer Verlag,2007,660-669
[82] Li C, Li X, Wang C, et al., A dependency aware task partitioning and schedulingalgorithm for hardware-software codesign on MPSoCs,12th International Conferenceon Algorithms and Architectures for Parallel Processing, ICA3PP2012, Fukuoka,Japan: Springer Verlag,2012,332-346
[83] Yu J, Hehua Z, Xun J, et al., Uncertain model and algorithm forhardware/software partitioning,2012IEEE Computer Society Annual Symposium onVLSI, ISVLSI2012, Amherst, Massachusetts, USA: IEEE Computer Society,2012,243-248
[84]郭天天，嵌入式系统软硬件划分技术研究：[博士学位论文]，国防科学技术大学，2006
[85] Herrmann D, Henkel J, Ernst R, An approach to the adaptation of estimated costparameters in the COSYMA system,3rd International Workshop onHardware/Software Codesign, Grenoble, FR: IEEE,1994,100-107
[86] Jagadeeswari M, Bhuvaneswari M C, Estimation of HW/SW cost parameters inAltera FPGA design environment, WSEAS Transactions on Information Science andApplications,2011,8(11):430-439
[87] Dick R P, Jha N K, MOGAC: A multiobjective genetic algorithm forhardware-software cosynthesis of distributed embedded systems, IEEE Transactionson Computer-Aided Design of Integrated Circuits and Systems,1998,17(10):920-935
[88] Stitt G, Lysecky R, Vahid F, Dynamic hardware/software partitioning: a firstapproach, Design Automation Conference, DAC2003, Anaheim, CA, USA: ACM,2003,250-255
[89] Waldeck P, Bergmann N, Dynamic hardware-software partitioning onreconfigurable system-on-chip,3rd IEEE International Workshop on System-On-Chipfor Real-time Applications, IWSOC2003, Calgary, Alberta, Canada: IEEE ComputerSociety,2003,102-105
[90] Lysecky R, Vahid F, A configurable logic architecture for dynamichardware/software partitioning, Design, Automation and Test in Europe Conferenceand Exhibition, Paris, France: Institute of Electrical and Electronics EngineersComputer Society,2004,480-485
[91] Le-Jun F, Bin L, Zhen-Quan Z, et al., An approach for dynamichardware/software partitioning based on DPBIL,3rd International Conference onNatural Computation, ICNC2007, Haikou, Hainan, China: Inst. of Elec. and Elec.Eng. Computer Society,2007,581-585
[92]黄瑜臣，吴强，陈宇等，面向RSoC的过程级动态软硬件划分，计算机工程与应用，2010，46（11）：67-69
[93] Tuffery P, Guyon F, Derreumaux P, Improved greedy algorithm for proteinstructure reconstruction, Journal of Computational Chemistry,2005,26(5):506-513
[94] He Z, Deng S, Xu X, et al., A fast greedy algorithm for outlier mining,10thPacific-Asia Conference on Advances in Knowledge Discovery and Data Mining,PAKDD2006, Singapore, Singapore: Springer Verlag,2006,567-576
[95] Guisheng Y, Guang Y, Wu Y, et al., Improvement of local greedy algorithm inGEAR,2007International Conference on Wireless Communications, Networking andMobile Computing, WiCOM2007, Shanghai, China: Inst. of Elec. and Elec. Eng.Computer Society,2007,2491-2494
[96]彭石宝，袁俊泉，向家彬，一种基于加权迭代贪婪算法的InSAR相位解缠的新方法，电子与信息学报，2008，30（6）：1326-1330
[97] Jin J, Gu Y, Mei S, An improved greedy algorithm for signal recovery fromrandom measurements,2010IEEE10th International Conference on SignalProcessing, ICSP2010, Beijing, China: Institute of Electrical and ElectronicsEngineers Inc.,2010,82-85
[98] Zhenhuan H, Research on improved greedy algorithm for train rescheduling,20117th International Conference on Computational Intelligence and Security, CIS2011, Sanya, Hainan, China: IEEE Computer Society,2011,1197-1200
[99] Arato P, Mann Z A, Orban A, Algorithmic aspects of hardware softwarepartitioning, ACM Transactions on Design Automation of Electronic Systems,2005,10(1):136-156
[100] Ammar H H, Tao Y, Fingerprint registration using genetic algorithms,3rd IEEESymposium on Application-Specific Systems and Software Engineering Technology,ASSET2000, Richardson Texas: IEEE Computer Society,2000,148-154
[101] Potts J C, Giddens T D, Yadav S B, Development and evaluation of animproved genetic algorithm based on migration and artificial selection, IEEETransactions on Systems, Man and Cybernetics,1994,24(1):73-86
[102] Ikuno Y, Kawabata H, Shirao Y, et al., Application of an improved geneticalgorithm to the learning of neural networks, Solid State Communications,1994,91(3):731-735
[103] Nara K, Improved genetic algorithm for large scale distribution systems lossminimum problem, the1995IEEE International Conference on EvolutionaryComputation, Perth, Aust: IEEE,1995,120-125
[104] Wang K, Qian Y, Yuan Y, et al., Synthesis and optimization of heat integrateddistillation systems using an improved genetic algorithm, Computers and ChemicalEngineering,1998,23(1):125-136
[105] Park J, Park Y, Won J, et al., Improved genetic algorithm for generationexpansion planning, IEEE Transactions on Power Systems,2000,15(3):916-922
[106]孙国玺，尹俊勋，改进遗传算法应用于静态MDR问题，哈尔滨工业大学学报，2005，37（10）：1433-1435
[107] Jiang L, Liu B, Zeng L, et al., Research on the omni-directional mobilemanipulator motion planning based on improved genetic algorithm,2009IEEEInternational Conference on Automation and Logistics, ICAL2009, Shenyang, China:IEEE Computer Society,2009,1921-1926
[108]方水良，姚嫣菲，赵诗奎，柔性车间调度的改进遗传算法，浙江大学学报(工学版)，2012，46（4）：629-635
[109] Dorigo M, Di Caro G, Ant colony optimization: a new meta-heuristic, the1999Congress on Evolutionary Computation, CEC99, Washington D.C. USA: IEEENeural Network Council,1999,1470-1477
[110] Stuetzle T, Hoos H, MAX-MIN Ant System and local search for the travelingsalesman problem, the1997IEEE International Conference on EvolutionaryComputation, ICEC'97, Indianapolis, IN, USA: IEEE,1997,309-314
[111] Bullnheimer B, Hartl R F, Strau C, A new rank based version of the ant system:a computational study, Central European Journal for Operations Research andEconomics,1997,7:25-38
[112] Hu X, Zhang J, Li Y, Orthogonal methods based ant colony search for solvingcontinuous optimization problems, Journal of Computer Science and Technology,2008,23(1):2-18
[113] Kennedy J, Eberhart R, Particle swarm optimization, IEEE InternationalConference on Neural Networks, Perth, Aust: IEEE,1995,1942-1948
[114] Zhang X, Li T, Improved particle swarm optimization algorithm for2D proteinfolding prediction,20071st International Conference on Bioinformatics andBiomedical Engineering, ICBBE2007, Wuhan, China: Inst. of Elec. and Elec. Eng.Computer Society,2007,53-56
[115]孔力，程晶晶，宋胜利等，基于改进粒子群优化技术的拜耳法物料平衡计算，华中科技大学学报（自然科学版），2008，36（1）：95-98
[116] Li M, Li W, Wang Y, et al., Blind source separation based on improved particleswarm optimization,2009International Conference on Artificial Intelligence andComputational Intelligence, AICI2009, Shanghai, China: IEEE Computer Society,2009,307-310
[117] Chaoli S, Jianchao Z, Shuchuan C, et al., Solving constrained optimizationproblems by an improved particle swarm optimization,2nd International Conferenceon Innovations in Bio-inspired Computing and Applications, IBICA2011, Shenzhen,Guangdong, China: IEEE Computer Society,2011,124-128
[118] Guo J, Tang S, Xu Q, An improved particle swarm optimization and itsapplication in maneuvering control laws design of the unmanned aerial vehicle,20128th International Conference on Natural Computation, ICNC2012, Chongqing, China:IEEE Computer Society,2012,1107-1111
[119] Yang M, Gu G, Zhu L, Parameter identification of the generalizedPrandtl-Ishlinskii model for piezoelectric actuators using modified particle swarmoptimization, Sensors and Actuators, A: Physical,2013,189:33-44
[120] Karaboga D, An idea based on honey bee swarm for numerical optimization:Technical Report-TR06,2005,1-10
[121] Quan H, Shi X, On the analysis of performance of the improvedartificial-bee-colony algorithm,4th International Conference on Natural Computation,ICNC2008, Jinan, China: Inst. of Elec. and Elec. Eng. Computer Society,2008,654-658
[122] Narasimhan H, Parallel artificial bee colony (PABC) algorithm,2009WorldCongress on Nature and Biologically Inspired Computing, NABIC2009, Coimbatore,India: IEEE Computer Society,2009,306-311
[123] Yao B, Yang C, Hu J, et al., An improved artificial bee colony algorithm for jobshop problem,2010International Conference on Advanced Mechanical Engineering,AME2010, Luoyang, China: Trans Tech Publications,2010,657-660
[124] Zhang Y, Wu L, Wang S, Magnetic resonance brain image classification by animproved artificial bee colony algorithm, Progress in Electromagnetics Research,2011,116:65-79
[125] Shi Y, Meng F, Shen G, A modified artificial bee colony algorithm for vehiclerouting problems with time windows, Information Technology Journal,2012,11(10):1490-1495
[126]李晓磊，邵之江，钱积新，一种基于动物自治体的寻优模式:鱼群算法，系统工程理论与实践，2002，22（11）：32-38
[127]李晓磊，路飞，田国会等，组合优化问题的人工鱼群算法应用，山东大学学报：工学版，2004，34（5）：64-67
[128] Lopez-Vallejo M, Lopez J C, On the hardware-software partitioning problem:system modeling and partitioning techniques, ACM Transactions on DesignAutomation of Electronic Systems,2003,8(3):269-297
[129]崔文华，刘晓冰，王伟等，混合蛙跳算法研究综述，控制与决策，2012，27（4）：481-486
[130] Eusuff M M, Lansey K E, Optimization of water distribution network designusing the shuffled frog leaping algorithm, Journal of Water Resources Planning andManagement,2003,129(3):210-225
[131] Selvakumar K, Vignesh R S, Vijayabalan R, Shuffled Frog Leaping Algorithmfor solving profit based unit commitment problem,2012International Conference onComputing, Communication and Applications, ICCCA2012, Dindigul, Tamilnadu,India: IEEE Computer Society,2012,1-6
[132] Topcuoglu H, Hariri S, Wu M, Performance-effective and low-complexity taskscheduling for heterogeneous computing, IEEE Transactions on Parallel andDistributed Systems,2002,13(3):260-274
[133] Boeres C, Chochia G, Thanisch P, On the scope of applicability of the ETFalgorithm,2nd International Workshop, IRREGULAR'95, Lyon, France:Springer-Verlag GmbH&Company KG,1995,159
[134] Sih G C, Lee E A, Compile-time scheduling heuristic forinterconnection-constrained heterogeneous processor architectures, IEEETransactions on Parallel and Distributed Systems,1993,4(2):175-187
[135] Yang T, Gerasoulis A, DSC: Scheduling parallel tasks on an unbounded numberof processors, IEEE Transactions on Parallel and Distributed Systems,1994,5(9):951-967
[136] Yuan M, Gu Z, He X, et al., Hardware/software partitioning and pipelinedscheduling on runtime reconfigurable FPGAs, ACM Transactions on DesignAutomation of Electronic Systems,2010,15(2):1-41
[137] Elfeky M G, Aref W G, Elmagarmid A K, Periodicity detection in time seriesdatabases, IEEE Transactions on Knowledge and Data Engineering,2005,17(7):875-887
[2] Ye H, Wu J, Computing models and algorithms for complex co-design systems,Journal of the University of Electronic Science and Technology of China,2011,40(3):333-345
[3] Abdelhalim M B, Habib S E D, An integrated high-level hardware/softwarepartitioning methodology, Design Automation for Embedded Systems,2011,15(1):19-50
[4]于苏东，刘雷波，尹首一等，嵌入式粗颗粒度可重构处理器的软硬件协同设计流程，电子学报，2009，37（5）：1136-1140
[5] Knudsen P V, Madsen J, PACE: A dynamic programming algorithm forhardware/software partitioning,4th International Workshop on Hardware/SoftwareCo-Design, Codes/CASHE'96, Pittsburgh, PA, USA: IEEE,1996,85-92
[6] Shrivastava A, Kumar M, Kapoor S, et al., Optimal hardware/software partitioningfor concurrent specification using dynamic programming, The13th InternationalConference on VLSI Design: Wireless and Digital Imaging in the Millennium,Calcutta, India: IEEE,2000,110-113
[7] Chang J, Pedram M, Codex-dp: co-design of communicating systems usingdynamic programming, IEEE Transactions on Computer-Aided Design of IntegratedCircuits and Systems,2000,19(7):732-744
[8] Wu J, Srikanthan T, Low-complex dynamic programming algorithm forhardware/software partitioning, Information Processing Letters,2006,98(2):41-46
[9] Niemann R, Marwedel P, Algorithm for hardware/software partitioning usingmixed integer linear programming, Design Automation for Embedded Systems,1997,2(2):165-193
[10] Kuang S, Chen C, Liao R, Partitioning and pipelined scheduling of embeddedsystem using integer linear programming,11th International Conference on Paralleland Distributed Systems Workshops, ICPADS2005, Fukuoka, Japan: Institute ofElectrical and Electronics Engineers Computer Society,2005,37-41
[11] Binh N N, Imai M, Shiomi A, et al., Hardware/software partitioning algorithmfor designing pipelined ASIPs with least gate counts,33rd Annual Design AutomationConference, Las Vegas, NV, USA: IEEE,1996,527-532
[12] Alomary A Y, Hardware/software codesign partitioner for ASIP design,3rdIEEE International Conference on Electronics, Circuits, and Systems, ICECS1996,Rodos, Greece: IEEE,1996,251-254
[13] Chatha K S, Vemuri R, Hardware-software partitioning and pipelined schedulingof transformative applications, IEEE Transactions on Very Large Scale Integration(VLSI) Systems,2002,10(3):193-208
[14] Jigang W, Thambipillai S, A branch-and-bound algorithm for hardware/softwarepartitioning,4th IEEE International Symposium on Signal processing and InformationTechnology, ISSPIT2004, Rome, Italy: Institute of Electrical and ElectronicsEngineers Inc.,2004,526-529
[15]盛蓝平，林涛，采用启发式分支定界的软硬件划分，计算机辅助设计与图形学学报，2005，17（3）：414-417
[16] Mann Z A, Orban A, Arato P, Finding optimal hardware/software partitions,Formal Methods in System Design,2007,31(3):241-263
[17] Jigang W, Chang B, Srikanthan T, A hybrid branch-and-bound strategy forhardware/software partitioning,8th IEEE/ACIS International Conference onComputer and Information Science, ICIS2009, Shanghai, China: IEEE ComputerSociety,2009,641-644
[18] Zhang Y, Kandemir M, A hardware-software codesign strategy for loop intensiveapplications,2009IEEE7th Symposium on Application Specific Processors, SASP2009, San Francisco, CA, United states: IEEE Computer Society,2009,107-113
[19] Wu J, Srikanthan T, Guang C, Algorithmic aspects of hardware/softwarepartitioning:1D search algorithms, IEEE Transactions on Computers,2010,59(4):532-544
[20] Saha D, Mitra R S, Basu A, Hardware software partitioning using geneticalgorithm, the199710th International Conference on VLSI Design, Hyderabad, India:IEEE,1997,155-160
[21] Harkin J, Mcginnity T M, Maguire L P, Genetic algorithm drivenhardware-software partitioning for dynamically reconfigurable embedded systems,Microprocessors and Microsystems,2001,25(5):263-274
[22] Farahani A F, Kamal M, Salmani-Jelodar M, Parallel-genetic-algorithm-basedHW/SW partitioning, International Symposium on Parallel Computing in ElectricalEngineering, PARELEC2006, Bialystok, Poland: IEEE Computer Society,2006,337-342
[23] Mudry P, Zufferey G, Tempesti G, A dynamically constrained genetic algorithmfor hardware-software partitioning,8th Annual Genetic and EvolutionaryComputation Conference, Seattle, WA, United states: Association for ComputingMachinery,2006,769-775
[24] Arunachalam V, Sapra S, Chaitanya N S K, et al., Hardware/softwarepartitioning algorithm for embedded systems with repeated functionalities,2008IEEERegion10Conference, TENCON2008, Hyderabad, India: Institute of Electrical andElectronics Engineers Inc.,2008,1-6
[25] Lee T, Fan Y, Cheng Y, et al., Hardware-software partitioning for embeddedmultiprocessor FPGA systems, International Journal of Innovative Computing,Information and Control,2009,5(10):3071-3083
[26]罗胜钦，马萧萧，陆忆，基于改进的NSGA遗传算法的SOC软硬件划分方法，电子学报，2009，37（11）：2595-2599
[27] Zheng S, Zhang Y, He T, The application of genetic algorithm in embeddedsystem hardware-software partitioning,2009International Conference on ElectronicComputer Technology, ICECT2009, Macau, China: Inst. of Elec. and Elec. Eng.Computer Society,2009,219-222
[28] Li L, Hongjun H, Qiang D, et al., Hardware/software partitioning forheterogeneous multicore SoC using genetic algorithm,2nd International Conferenceon Intelligent System Design and Engineering Application, ISDEA2012, Sanya,Hainan, China: IEEE Computer Society,2012,1267-1270
[29] Lin T, Sait S M, Cyre W R, Buffer size driven partitioning for HW/SW co-design,the1998IEEE International Conference on Computer Design, Austin, TX, USA:IEEE,1998,596-601
[30] Purnaprajna M, Reformat M, Pedrycz W, Genetic algorithms inhardware-software partitioning, the International Conference on Engineering ofReconfigurable Systems and Algorithms, ERSA'04, Las Vegas, NV, United states:CSREA Press,2004,123-129
[31] Purnaprajna M, Reformat M, Pedrycz W, Genetic algorithms forhardware-software partitioning and optimal resource allocation, Journal of SystemsArchitecture,2007,53(7):339-354
[32] Jagadeeswari M, Bhuvaneswari M C, Efficient multi-objective genetic algorithmfor hardware-software partitioning in embedded system design: ENGA, InternationalJournal of Computer Applications in Technology,2009,36(3-4):181-190
[33] Fu Y, Liu X, Guo P, A multi-objective optimization genetic algorithm for SOPChardware-software partitioning,2011International Conference on AdvancedMaterials and Engineering Materials, ICAMEM2011, Shenyang, Liaoning, China:Trans Tech Publications,2012,1142-1148
[34] Chehida K B, Auguin M, HW/SW partitioning approach for reconfigurablesystem design,2002International Conference on Compilers, Architecture, andSynthesis for Embedded Systems, CASES '02, Grenoble, France: Association forComputing Machinery,2002,247-251
[35] Zou Y, Zhuang Z, Chen H, HW-SW partitioning based on genetic algorithm, the2004Congress on Evolutionary Computation, CEC2004, Portland, OR, United states:Institute of Electrical and Electronics Engineers Inc.,2004,628-633
[36] Dou S, Ding S, Zhang S, et al., GA-based algorithm for hardware/softwarepartitioning with resource contentions,2010IEEE International Conference onAdvanced Computer Control, ICACC2010, New Jersey, United States: IEEEComputer Society,2010,68-72
[37]郭晓东，刘积仁，一种基于模拟退火算法的硬件/软件分解方法，东北大学学报：自然科学版，2000，21（3）：233-236
[38] Eles P, Peng Z, Kuchcinski K, et al., System level hardware/software partitioningbased on simulated annealing and tabu search, Design Automation for EmbeddedSystems,1997,2(1):5-32
[39] Eles P, Peng Z, Kuchcinski K, et al., Hardware/software partitioning withiterative improvement heuristics,9th International Symposium on System Synthesis,ISSS'96, La Jolla, CA, USA: IEEE,1996,71-76
[40]彭艺频，凌明，杨军，性能受限系统的软硬件划分方法，东南大学学报：自然科学版，2004，34（6）：828-832
[41] Zebo P, Kuchcinski K, An algorithm for partitioning of application specificsystems,4th European Conference on Design Automation with the European Event inASIC Design, EDAC1993, Paris, Fr: Publ by IEEE,1993,316-321
[42] Abdelhalim M B, Salama A E, Habib S E D, Hardware software partitioningusing particle swarm optimization technique,6th IEEE International Workshop onSystem on Chip for Real Time Applications, IWSOC2006, Cairo, Egypt: Inst. of Elec.and Elec. Eng. Computer Society,2006,189-194
[43] Abdelhalim M B, Habib S E D, Modeling communication cost and hardwarealternatives in PSO based HW/SW partitioning,19th International Conference onMicroelectronics, ICM2007, Cairo, Egypt: Institute of Electrical and ElectronicsEngineers Inc.,2007,111-114
[44] Farmahini-Farahani A, Kamal M, Fakhraie S M, et al., HW/SW partitioningusing discrete particle swarm,17th Great Lakes Symposium on VLSI, GLSVLSI'07,Stresa-Lago Maggiore, Italy: Association for Computing Machinery,2007,359-364
[45] Bhattacharya A, Konar A, Das S, et al., Hardware software partitioning problemin embedded system design using particle swarm optimization algorithm,2ndInternational Conference on Complex, Intelligent and Software IntensiveSystems,CISIS2008, Barcelona, Spain: Inst. of Elec. and Elec. Eng. ComputerSociety,2008,171-176
[46] Qiaoling T, Xuecheng Z, Qiao Z, et al., The hardware/software partitioning inembedded system by improved particle swarm optimization algorithm, The5th IEEEInternational Symposium on Embedded Computing, SEC2008, Beijing, China: Inst.of Elec. and Elec. Eng. Computer Society,2008,43-46
[47] Yuan J, Peng M, Hardware/Software partitioning algorithm based on waveletmutation binary particle swarm optimization,2011IEEE3rd International Conferenceon Communication Software and Networks, ICCSN2011, Xi'an, China: IEEEComputer Society,2011,347-350
[48] Zhao H, Weng X W, Chen C, et al., Research on hardware/software partition offuture transfiguration aircraft store management system,201224th Chinese Controland Decision Conference, CCDC2012, Taiyuan, China: IEEE Computer Society,2012,483-487
[49] Ahmed U, Khan G N, Embedded system partitioning with flexible granularity byusing a variant of Tabu Search, Canadian Conference on Electrical and ComputerEngineering, CCECE2004, Niagara Falls, Canada: Institute of Electrical andElectronics Engineers Inc.,2004,2073-2076
[50] Pu G, Chong Z, Qiu Z, et al., A hybrid heuristic algorithm for HW-SWpartitioning within timed automata,10th International Conference onKnowledge-Based Intelligent Information and Engineering Systems, KES2006,Bournemouth, United kingdom: Springer Verlag,2006,459-466
[51] Pu G, Chong Z, Qiu Z, et al., Integrating timed automata into tabu algorithm forHW-SW partitioning,11th IEEE International Conference on Engineering ofComplex Computer Systems, ICECCS2006, Stanford, CA, United states: Institute ofElectrical and Electronics Engineers Inc.,2006,131-138
[52] Wu J, Srikanthan T, Lei T, Efficient heuristic algorithms for path-basedhardware/software partitioning, Mathematical and Computer Modelling,2010,51(7-8):974-984
[53] Wu J, Sun Q, Srikanthan T, Algorithmic aspects for multiple-choicehardware/software partitioning, Computers and Operations Research,2012,39(12):3281-3292
[54] Yu H, Fan X, Zhang S, et al., A guiding function based greedy partitioningalgorithm for dynamically reconfigurable systems,8th International Conference onSolid-State and Integrated Circuit Technology, ICSICT2006, Shanghai, China: Inst.of Elec. and Elec. Eng. Computer Society,2007,2009-2012
[55] Wang H, Zhang H, Improved HW/SW partitioning algorithm on efficient use ofhardware resource,2nd International Conference on Computer and AutomationEngineering, ICCAE2010, Singapore, Singapore: IEEE Computer Society,2010,682-685
[56] Li N, Fang Y, Software/hardware partition in multiple processors embeddedsystem, International Conference on Machine Learning and Cybernetics, ICMLC2005, Guangzhou, China: Institute of Electrical and Electronics Engineers ComputerSociety,2005,165-170
[57] Li S, Wang D, Li T, et al., Distributed collaborative partition method ofreconfigurable SoC using ant colony optimization,11th International Conference onComputer Supported Cooperative Work in Design, CSCWD2007, Melbourne, VIC,Australia: Inst. of Elec. and Elec. Eng. Computer Society,2007,133-138
[58] Wang D, Li S, Dou Y, Collaborative hardware/software partition ofcoarse-grained reconfigurable system using evolutionary ant colony optimization,2008Asia and South Pacific Design Automation Conference, ASP-DAC2008, Seoul,Korea, Republic of: Institute of Electrical and Electronics Engineers Inc.,2008,679-684
[59]张煜东，吴乐南，韦耿等，基于自适应蚁群算法的软硬件划分，控制与决策，2009，24（9）：1385-1389
[60] Ferrandi F, Pilato C, Sciuto D, et al., Mapping and scheduling of parallel Capplications with ant colony optimization onto heterogeneous reconfigurable MPSoCs,201015th Asia and South Pacific Design Automation Conference, ASP-DAC2010,Taipei, Taiwan: Institute of Electrical and Electronics Engineers Inc.,2010,799-804
[61] Liu Y, Li Q C, Liu J X, et al., Study on hardware software partitioning usingimmune algorithm and its convergence property,2009IEEE International Conferenceon Intelligent Computing and Intelligent Systems, ICIS2009, Shanghai, China: IEEEComputer Society,2009,4-8
[62]邢冀鹏，邹雪城，刘政林等，基于混沌优化算法的软硬件划分，华中科技大学学报：自然科学版，2006，34（11）：61-63
[63] Vahid F, Modifying min-cut for hardware and software functional partitioning,the19975th International Workshop on Hardware/Software Codesign,CODES/CASHE'97, Braunschweig, Ger: IEEE,1997,43-48
[64] Vahid F, Le T D, Extending the Kernighan/Lin heuristic for hardware andsoftware functional partitioning, Design Automation for Embedded Systems,1997,2(2):237-261
[65]郭兵，沈艳，王典辉等，一种基于离散Hopfield神经网络的SoC嵌入式操作系统软/硬件划分方法，四川大学学报：工程科学版，2006，38（5）：122-127
[66] Guo B, Shen Y, Hardware-software partitioning of embedded operating systemin the SoC using a discrete hopfield neural network approach, Chinese Journal ofElectronics,2007,16(1):13-17
[67] Guo B, Shen Y, Huang Y, et al., A novel discrete hopfield neural networkapproach for hardware-software partitioning of RTOS in the SoC, Embedded andUbiquitous Computing Workshops, EUC2006, Seoul, Korea, Republic of: SpringerVerlag,2006,888-897
[68] Li L, Song Y, Gao M, A new genetic simulated annealing algorithm forhardware-software partitioning,2nd International Conference on Information Scienceand Engineering, ICISE2010, Hangzhou, China: IEEE Computer Society,2010,1-4
[69]熊志辉，李恩昆，陈吉华，遗传算法与蚂蚁算法动态融合的软硬件划分，软件学报，2005，16（4）：503-512
[70] Zhao X, Li L, Gao M, Research on hardware-software partitioning method fordynamically reconfigurable embedded system,2012International Applied Mechanics,MechatronicsAutomation and System Simulation Meeting, AMMASS2012,Hangzhou, China: Trans Tech Publications,2012,606-610
[71]刘安，冯金富，梁晓龙等，基于遗传粒子群优化的嵌入式系统软硬件划分算法，计算机辅助设计与图形学学报，2010，22（6）：927-933
[72] Cui L, A novel approach to hardware/software partitioning for reconfigurableembedded systems, Journal of Computers (Finland),2012,7(10SPL.ISS.):2518-2525
[73] Wu Y, Zhang H, Yang H, Research on parallel HW/SW partitioning based onhybrid PSO algorithm,9th International Conference on Algorithms and Architecturesfor Parallel Processing, ICA3PP2009, Taipei, Taiwan: Springer Verlag,2009,449-459
[74] Eimuri T, Salehi S, Using DPSO and B&B algorithms for Hardware/Softwarepartitioning in co-design,2nd International Conference on Computer Research andDevelopment, ICCRD2010, Kuala Lumpur, Malaysia: IEEE Computer Society,2010,416-420
[75] Luo L, He H, Liao C, et al., Hardware/software partitioning for heterogeneousmulticore SOC using Particle Swarm Optimization and Immune Clone (PSO-IC)algorithm,2010IEEE International Conference on Information and Automation, ICIA2010, Harbin, Heilongjiang, China: IEEE Computer Society,2010,490-494
[76] Ma T, Yang J, Wang X, Low power hardware-software partitioning algorithm forheterogeneous distributed embedded systems, International Conference on Embeddedand Ubiquitous Computing, EUC2006, Seoul, Korea, Republic of: Springer Verlag,2006,702-711
[77] Ma T, Li Z, Yang J, A novel neural network search for energy-efficienthardware-software partitioning,2006International Conference on Machine Learningand Cybernetics, Dalian, China: Inst. of Elec. and Elec. Eng. Computer Society,2006,3053-3058
[78] Liu P, Wu J, Wang Y, Hybrid algorithms for hardware/software partitioning andscheduling on reconfigurable devices, Mathematical and Computer Modelling,2012:In Press
[79] Pan Z, Li W, Shao Q, et al., Hardware-software partitioning for the design ofsystem on chip by neural network optimization method,7th International Symposiumon Precision Engineering Measurements and Instrumentation, Lijiang, China: SPIE,2011
[80] Strachacki M, Speedup of branch and bound method for hardware/softwarepartitioning,20081st International Conference on Information Technology, IT2008,Gdansk, Poland: Inst. of Elec. and Elec. Eng. Computer Society,2008,1-4
[81] Huang Y, Kim Y, Applying hybrid neural fuzzy system to embedded systemhardware/software partitioning,3rd International Conference on IntelligentComputing, ICIC2007, Qingdao, China: Springer Verlag,2007,660-669
[82] Li C, Li X, Wang C, et al., A dependency aware task partitioning and schedulingalgorithm for hardware-software codesign on MPSoCs,12th International Conferenceon Algorithms and Architectures for Parallel Processing, ICA3PP2012, Fukuoka,Japan: Springer Verlag,2012,332-346
[83] Yu J, Hehua Z, Xun J, et al., Uncertain model and algorithm forhardware/software partitioning,2012IEEE Computer Society Annual Symposium onVLSI, ISVLSI2012, Amherst, Massachusetts, USA: IEEE Computer Society,2012,243-248
[84]郭天天，嵌入式系统软硬件划分技术研究：[博士学位论文]，国防科学技术大学，2006
[85] Herrmann D, Henkel J, Ernst R, An approach to the adaptation of estimated costparameters in the COSYMA system,3rd International Workshop onHardware/Software Codesign, Grenoble, FR: IEEE,1994,100-107
[86] Jagadeeswari M, Bhuvaneswari M C, Estimation of HW/SW cost parameters inAltera FPGA design environment, WSEAS Transactions on Information Science andApplications,2011,8(11):430-439
[87] Dick R P, Jha N K, MOGAC: A multiobjective genetic algorithm forhardware-software cosynthesis of distributed embedded systems, IEEE Transactionson Computer-Aided Design of Integrated Circuits and Systems,1998,17(10):920-935
[88] Stitt G, Lysecky R, Vahid F, Dynamic hardware/software partitioning: a firstapproach, Design Automation Conference, DAC2003, Anaheim, CA, USA: ACM,2003,250-255
[89] Waldeck P, Bergmann N, Dynamic hardware-software partitioning onreconfigurable system-on-chip,3rd IEEE International Workshop on System-On-Chipfor Real-time Applications, IWSOC2003, Calgary, Alberta, Canada: IEEE ComputerSociety,2003,102-105
[90] Lysecky R, Vahid F, A configurable logic architecture for dynamichardware/software partitioning, Design, Automation and Test in Europe Conferenceand Exhibition, Paris, France: Institute of Electrical and Electronics EngineersComputer Society,2004,480-485
[91] Le-Jun F, Bin L, Zhen-Quan Z, et al., An approach for dynamichardware/software partitioning based on DPBIL,3rd International Conference onNatural Computation, ICNC2007, Haikou, Hainan, China: Inst. of Elec. and Elec.Eng. Computer Society,2007,581-585
[92]黄瑜臣，吴强，陈宇等，面向RSoC的过程级动态软硬件划分，计算机工程与应用，2010，46（11）：67-69
[93] Tuffery P, Guyon F, Derreumaux P, Improved greedy algorithm for proteinstructure reconstruction, Journal of Computational Chemistry,2005,26(5):506-513
[94] He Z, Deng S, Xu X, et al., A fast greedy algorithm for outlier mining,10thPacific-Asia Conference on Advances in Knowledge Discovery and Data Mining,PAKDD2006, Singapore, Singapore: Springer Verlag,2006,567-576
[95] Guisheng Y, Guang Y, Wu Y, et al., Improvement of local greedy algorithm inGEAR,2007International Conference on Wireless Communications, Networking andMobile Computing, WiCOM2007, Shanghai, China: Inst. of Elec. and Elec. Eng.Computer Society,2007,2491-2494
[96]彭石宝，袁俊泉，向家彬，一种基于加权迭代贪婪算法的InSAR相位解缠的新方法，电子与信息学报，2008，30（6）：1326-1330
[97] Jin J, Gu Y, Mei S, An improved greedy algorithm for signal recovery fromrandom measurements,2010IEEE10th International Conference on SignalProcessing, ICSP2010, Beijing, China: Institute of Electrical and ElectronicsEngineers Inc.,2010,82-85
[98] Zhenhuan H, Research on improved greedy algorithm for train rescheduling,20117th International Conference on Computational Intelligence and Security, CIS2011, Sanya, Hainan, China: IEEE Computer Society,2011,1197-1200
[99] Arato P, Mann Z A, Orban A, Algorithmic aspects of hardware softwarepartitioning, ACM Transactions on Design Automation of Electronic Systems,2005,10(1):136-156
[100] Ammar H H, Tao Y, Fingerprint registration using genetic algorithms,3rd IEEESymposium on Application-Specific Systems and Software Engineering Technology,ASSET2000, Richardson Texas: IEEE Computer Society,2000,148-154
[101] Potts J C, Giddens T D, Yadav S B, Development and evaluation of animproved genetic algorithm based on migration and artificial selection, IEEETransactions on Systems, Man and Cybernetics,1994,24(1):73-86
[102] Ikuno Y, Kawabata H, Shirao Y, et al., Application of an improved geneticalgorithm to the learning of neural networks, Solid State Communications,1994,91(3):731-735
[103] Nara K, Improved genetic algorithm for large scale distribution systems lossminimum problem, the1995IEEE International Conference on EvolutionaryComputation, Perth, Aust: IEEE,1995,120-125
[104] Wang K, Qian Y, Yuan Y, et al., Synthesis and optimization of heat integrateddistillation systems using an improved genetic algorithm, Computers and ChemicalEngineering,1998,23(1):125-136
[105] Park J, Park Y, Won J, et al., Improved genetic algorithm for generationexpansion planning, IEEE Transactions on Power Systems,2000,15(3):916-922
[106]孙国玺，尹俊勋，改进遗传算法应用于静态MDR问题，哈尔滨工业大学学报，2005，37（10）：1433-1435
[107] Jiang L, Liu B, Zeng L, et al., Research on the omni-directional mobilemanipulator motion planning based on improved genetic algorithm,2009IEEEInternational Conference on Automation and Logistics, ICAL2009, Shenyang, China:IEEE Computer Society,2009,1921-1926
[108]方水良，姚嫣菲，赵诗奎，柔性车间调度的改进遗传算法，浙江大学学报(工学版)，2012，46（4）：629-635
[109] Dorigo M, Di Caro G, Ant colony optimization: a new meta-heuristic, the1999Congress on Evolutionary Computation, CEC99, Washington D.C. USA: IEEENeural Network Council,1999,1470-1477
[110] Stuetzle T, Hoos H, MAX-MIN Ant System and local search for the travelingsalesman problem, the1997IEEE International Conference on EvolutionaryComputation, ICEC'97, Indianapolis, IN, USA: IEEE,1997,309-314
[111] Bullnheimer B, Hartl R F, Strau C, A new rank based version of the ant system:a computational study, Central European Journal for Operations Research andEconomics,1997,7:25-38
[112] Hu X, Zhang J, Li Y, Orthogonal methods based ant colony search for solvingcontinuous optimization problems, Journal of Computer Science and Technology,2008,23(1):2-18
[113] Kennedy J, Eberhart R, Particle swarm optimization, IEEE InternationalConference on Neural Networks, Perth, Aust: IEEE,1995,1942-1948
[114] Zhang X, Li T, Improved particle swarm optimization algorithm for2D proteinfolding prediction,20071st International Conference on Bioinformatics andBiomedical Engineering, ICBBE2007, Wuhan, China: Inst. of Elec. and Elec. Eng.Computer Society,2007,53-56
[115]孔力，程晶晶，宋胜利等，基于改进粒子群优化技术的拜耳法物料平衡计算，华中科技大学学报（自然科学版），2008，36（1）：95-98
[116] Li M, Li W, Wang Y, et al., Blind source separation based on improved particleswarm optimization,2009International Conference on Artificial Intelligence andComputational Intelligence, AICI2009, Shanghai, China: IEEE Computer Society,2009,307-310
[117] Chaoli S, Jianchao Z, Shuchuan C, et al., Solving constrained optimizationproblems by an improved particle swarm optimization,2nd International Conferenceon Innovations in Bio-inspired Computing and Applications, IBICA2011, Shenzhen,Guangdong, China: IEEE Computer Society,2011,124-128
[118] Guo J, Tang S, Xu Q, An improved particle swarm optimization and itsapplication in maneuvering control laws design of the unmanned aerial vehicle,20128th International Conference on Natural Computation, ICNC2012, Chongqing, China:IEEE Computer Society,2012,1107-1111
[119] Yang M, Gu G, Zhu L, Parameter identification of the generalizedPrandtl-Ishlinskii model for piezoelectric actuators using modified particle swarmoptimization, Sensors and Actuators, A: Physical,2013,189:33-44
[120] Karaboga D, An idea based on honey bee swarm for numerical optimization:Technical Report-TR06,2005,1-10
[121] Quan H, Shi X, On the analysis of performance of the improvedartificial-bee-colony algorithm,4th International Conference on Natural Computation,ICNC2008, Jinan, China: Inst. of Elec. and Elec. Eng. Computer Society,2008,654-658
[122] Narasimhan H, Parallel artificial bee colony (PABC) algorithm,2009WorldCongress on Nature and Biologically Inspired Computing, NABIC2009, Coimbatore,India: IEEE Computer Society,2009,306-311
[123] Yao B, Yang C, Hu J, et al., An improved artificial bee colony algorithm for jobshop problem,2010International Conference on Advanced Mechanical Engineering,AME2010, Luoyang, China: Trans Tech Publications,2010,657-660
[124] Zhang Y, Wu L, Wang S, Magnetic resonance brain image classification by animproved artificial bee colony algorithm, Progress in Electromagnetics Research,2011,116:65-79
[125] Shi Y, Meng F, Shen G, A modified artificial bee colony algorithm for vehiclerouting problems with time windows, Information Technology Journal,2012,11(10):1490-1495
[126]李晓磊，邵之江，钱积新，一种基于动物自治体的寻优模式:鱼群算法，系统工程理论与实践，2002，22（11）：32-38
[127]李晓磊，路飞，田国会等，组合优化问题的人工鱼群算法应用，山东大学学报：工学版，2004，34（5）：64-67
[128] Lopez-Vallejo M, Lopez J C, On the hardware-software partitioning problem:system modeling and partitioning techniques, ACM Transactions on DesignAutomation of Electronic Systems,2003,8(3):269-297
[129]崔文华，刘晓冰，王伟等，混合蛙跳算法研究综述，控制与决策，2012，27（4）：481-486
[130] Eusuff M M, Lansey K E, Optimization of water distribution network designusing the shuffled frog leaping algorithm, Journal of Water Resources Planning andManagement,2003,129(3):210-225
[131] Selvakumar K, Vignesh R S, Vijayabalan R, Shuffled Frog Leaping Algorithmfor solving profit based unit commitment problem,2012International Conference onComputing, Communication and Applications, ICCCA2012, Dindigul, Tamilnadu,India: IEEE Computer Society,2012,1-6
[132] Topcuoglu H, Hariri S, Wu M, Performance-effective and low-complexity taskscheduling for heterogeneous computing, IEEE Transactions on Parallel andDistributed Systems,2002,13(3):260-274
[133] Boeres C, Chochia G, Thanisch P, On the scope of applicability of the ETFalgorithm,2nd International Workshop, IRREGULAR'95, Lyon, France:Springer-Verlag GmbH&Company KG,1995,159
[134] Sih G C, Lee E A, Compile-time scheduling heuristic forinterconnection-constrained heterogeneous processor architectures, IEEETransactions on Parallel and Distributed Systems,1993,4(2):175-187
[135] Yang T, Gerasoulis A, DSC: Scheduling parallel tasks on an unbounded numberof processors, IEEE Transactions on Parallel and Distributed Systems,1994,5(9):951-967
[136] Yuan M, Gu Z, He X, et al., Hardware/software partitioning and pipelinedscheduling on runtime reconfigurable FPGAs, ACM Transactions on DesignAutomation of Electronic Systems,2010,15(2):1-41
[137] Elfeky M G, Aref W G, Elmagarmid A K, Periodicity detection in time seriesdatabases, IEEE Transactions on Knowledge and Data Engineering,2005,17(7):875-887