Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 211200075-6.doi: 10.11896/jsjkx.211200075

• Interdiscipline & Application • Previous Articles     Next Articles

Acceleration Method for Multidimensional Function Optimization Based on Artificial Bee Colony Algorithm

LI Hui1, HAN Lin2, YU Zhe3, WANG Wei2   

  1. 1 School of Economics,Qingdao Agricultural University,Qingdao,Shandong 266109,China
    2 National Supercomputing Center in Zhengzhou,Zhengzhou University ,Zhengzhou 450000,China
    3 Institute of Microelectronics of the Chinese Academy of Sciences,Beijing 100029,China
  • Online:2022-11-10 Published:2022-11-21
  • About author:LI Hui,born in 1978,Ph.D,lecturer.His main research inte-rests include risk management and actuarial and so on.
  • Supported by:
    Ultra-large-scale Computing Applications and Independent Software Development of Silicon Nanostructures and Chip Devices(201400211300).

PDF (PC)

251

Abstract: The artificial bee colony algorithm is widely used in the development of agricultural and rural big data applications,the serial artificial bee colony algorithm has a high time complexity and is not suitable for solving multi-dimensional problems quic-kly.According to the serial artificial bee colony algorithm,the problem of low execution efficiency of multi-dimensional function solving is analyzed,a multi-dimensional function optimization method based on the artificial bee colony algorithm is proposed after analyzing the multi-dimensional function and determining the artificial dependency relationship,which consists of task allocation,data distribution,synchronization operations and task parallelism.To demonstrate the efficacy of the proposed method,the Haiguang processor is used as a hardware test platform to compare and test four multi-dimensional functions.Experimental results show that the proposed method significantly outperforms the serial artificial bee colony algorithm in solving four multidimensional functions.

Key words: Big data, Artificial bee colony algorithm, Multidimensional function, ROCm HIP model, HYGON processor

CLC Number: 

  • TP391
[1]The State Council.Implementation Opinions of the Ministry ofAgriculture on Promoting the Development of Agricultural and Rural Big Data.[R/OL].(2015-09-30)[2016-04-10].http://www.gov.cn/gongbao/content/2016/content_5061698.htm.
[2]XU S,WANG W,ZHANG J,et al.High Performance Computing Algorithm and Software for Heterogeneous Computing[J].Journal of Software,2021,32(8):2365-2376.
[3]VIKHAR P A.Evolutionary algorithms:A critical review andits future prospects[C]//2016 International conference onglobal trends in signal processing.IEEE Computer Society,2016:261-265.
[4]AKHTARUZZAMAN M,SHAFIE A A,RAIHAN S M,et al.Golden ratio,the Phi,and its geometrical substantiation[C]//2011 IEEE Student Conference on Research and Development.ACM,2011:425-430.
[5]CHEN Y,BEAULIEU N C.A simple polynomial approximation to the Gaussian Q-function and its application[J].IEEE Communications Letters,2009,13(2):124-126.
[6]CHAKRABORTY A,KAR A K.Swarm intelligence:A review of algorithms[J].Nature-Inspired Computing and Optimization,2017,10(2):475-494.
[7]ZHAO R,LIU Q,LI C,et al.Performance Comparison and Application of Swarm Intelligence Algorithms in Crowd Evacuation[C]//Proceedings of the 2020 4th International Conference on Management Engineering.ACM,2020:47-51.
[8]KARABOGA D,BASTURK B.A powerful and efficient algorithm for numerical function optimization:artificial bee colony(ABC) algorithm[J].Journal of Global Optimization,2007,39(3):459-471.
[9]LUO G H,HUANG S K,CHANG Y S,et al.A parallel Bees Algorithm implementation on GPU[J].Journal of Systems Architecture,2014,60(3):271-279.
[10]BANHARNSAKUN A,ACHALAKUL T,SIRINAOVAKULB.Artificial bee colony algorithm on distributed environments[C]//2010 second world congress on nature and biologically inspired computing(NaBIC).IEEE Computer Society,2010:13-18.
[11]MUÑOZ D M,LLANOS C H,COELHO L S,et al.Accelerating the artificial bee colony algorithm by hardware parallel implementations[C]//2012 IEEE 3rd Latin American Symposium on Circuits and Systems(LASCAS).IEEE Computer Society,2012:1-4.
[12]KARABOGA D,AKAY B.A comparative study of artificial bee colony algorithm[J].Appl Math Comput,2009,214:108-132.
[13]KARABOGA D,AKAY B.A comparative study of artificial bee colony algorithm[J].Applied Mathematics and Computation,2009,214(1):108-132.
[14]GUO B X.Research on Photovoltaic Power Forecasting Based on Intelligent Water Drop Algorithm and Neural Network[D].Beijing:North China Electric Power University,2016.
[15]KANG S,QIAN X Z,GAN L.ParallelSaNSDE for Many-Core Sunway Processor[J].Journal of Frontiers of Computer Science and Technology,2021,15(10):2015-2024.
[16]YUAN L,ZHANG Y Q,BAI X R,et al.Research on Locality-aware Design Mechanism of State-of-the-art Parallel Programming Languages[J].Computer Science,2020,47(1):7-16.
[17]WANG Y C,HU H,WILLIA M,et al.Performance evaluation of Sugon exascale prototype with GTC-P[J].Computer Engineering & Science,2020,42(1):1-7.
[18]Introduction toamd gpu programming with hip [EB/OL].(2019-09-06) [2019-12-23].https://www.olcf.ornl.gov/wp-content/uploads/2019/09/AMD_GPU_HIP_training_20190906.pdf.
[19]LI J C.Research on Image Dehazing Heterogeneous Acceleration Method Based on FPGA+CPU[D].Xi’an:Xidian University,2017.
[20]CHEN P,ZHAO H L,TAO C,et al.Block-run-based connected component labelling algorithm for GPGPU using shared memory[J].Electronics Letters,2011,47(24):1309-1311.
[21]KARABOGA D,AKAY B,OZTURK C.Artificial bee colony(ABC) optimization algorithm for training feed-forward neural networks[C]//International Conference on Modeling Decisions for Artificial Intelligence.IEEE Computer Society,2007:318-329.
[1] SHAO Peng. FIR Low Pass Digital Filter Based on Multi-strategy Discrete Artificial Bee Colony Algorithm [J]. Computer Science, 2023, 50(6A): 220700026-5.
[2] XU Tianjie, WANG Pingxin, YANG Xibei. Three-way k-means Clustering Based on Artificial Bee Colony [J]. Computer Science, 2023, 50(6): 116-121.
[3] FAN Shuhuan, HOU Mengshu. Dataspace:A New Data Organization and Management Model [J]. Computer Science, 2023, 50(5): 115-127.
[4] HU Xuegang, LI Yang, WANG Lei, LI Peipei, YOU Zhuhong. Key Technologies of Intelligent Identification of Biomarkers:Review of Research on Association Prediction Between Circular RNA and Disease [J]. Computer Science, 2023, 50(4): 369-387.
[5] JIANG Chuanyu, HAN Xiangyu, YANG Wenrui, LYU Bohan, HUANG Xiaoou, XIE Xia, GU Yang. Survey of Medical Knowledge Graph Research and Application [J]. Computer Science, 2023, 50(3): 83-93.
[6] LU Mingchen, LYU Yanqi, LIU Ruicheng, JIN Peiquan. Fast Storage System for Time-series Big Data Streams Based on Waterwheel Model [J]. Computer Science, 2023, 50(1): 25-33.
[7] HE Qiang, YIN Zhen-yu, HUANG Min, WANG Xing-wei, WANG Yuan-tian, CUI Shuo, ZHAO Yong. Survey of Influence Analysis of Evolutionary Network Based on Big Data [J]. Computer Science, 2022, 49(8): 1-11.
[8] CHEN Jing, WU Ling-ling. Mixed Attribute Feature Detection Method of Internet of Vehicles Big Datain Multi-source Heterogeneous Environment [J]. Computer Science, 2022, 49(8): 108-112.
[9] WANG Mei-shan, YAO Lan, GAO Fu-xiang, XU Jun-can. Study on Differential Privacy Protection for Medical Set-Valued Data [J]. Computer Science, 2022, 49(4): 362-368.
[10] SUN Xuan, WANG Huan-xiao. Capability Building for Government Big Data Safety Protection:Discussions from Technologicaland Management Perspectives [J]. Computer Science, 2022, 49(4): 67-73.
[11] WANG Qing-xu, DONG Li-jun, JIA Wei, LIU Chao, YANG Guang, WU Tie-jun. Vector Representation and Computation Based Dynamic Access Control in Open Environment [J]. Computer Science, 2022, 49(11A): 210900217-7.
[12] LI Hui, HAN Lin, TAO Hong-wei, DONG Ben-song. Study on Office Password Recovery Vectorization Technology Based on Sunway Many-core Processor [J]. Computer Science, 2022, 49(11A): 210900176-5.
[13] ZHANG Kang-wei, ZHANG Jing-wei, YANG Qing, HU Xiao-li, SHAN Mei-jing. DCPFS:Distributed Companion Patterns Mining Framework for Streaming Trajectories [J]. Computer Science, 2022, 49(11A): 211100268-10.
[14] WANG Jun, WANG Xiu-lai, PANG Wei, ZHAO Hong-fei. Research on Big Data Governance for Science and Technology Forecast [J]. Computer Science, 2021, 48(9): 36-42.
[15] YU Yue-zhang, XIA Tian-yu, JING Yi-nan, HE Zhen-ying, WANG Xiao-yang. Smart Interactive Guide System for Big Data Analytics [J]. Computer Science, 2021, 48(9): 110-117.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.