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Parallel Implementation of kNN Algorithm for Breast Cancer Detection

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Book cover Evolution in Computational Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1176))

Abstract

Current advances in parallel processing technology aims at providing unmatched degree of computational power in upcoming days. Parallel computation is an efficient form of information processing which exploits the concurrency of execution. This paper investigates the use of parallel programming, when applied on k Nearest Neighbors (kNN) algorithm which is intended for classification and prediction of the large dataset. Breast cancer dataset is used for classification and prediction which consists of two labels namely, malignant and benign. kNN is a non-parametric algorithm which makes use of similarity measure to classify the dataset into different categories. The similarity between the data points is computed by using Euclidean distance formula. Multiple threads are created for parallel processing and an appropriate kNN graph is constructed, which helps in easier implementation. Finally, execution speeds for sequential and parallel programs is recorded. The results are verified by using frameworks namely, Message Passing Interface (MPI) and Compute Unified Device Architecture (CUDA) highlighting that parallel execution takes less time when compared to sequential execution.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India

    Suhas Athani, Shreesha Joshi, B. Ashwath Rao, Shwetha Rai & N. Gopalakrishna Kini

Authors
  1. Suhas Athani
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  2. Shreesha Joshi
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  3. B. Ashwath Rao
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  4. Shwetha Rai
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  5. N. Gopalakrishna Kini
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Corresponding author

Correspondence to B. Ashwath Rao .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  2. Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan

    Sheng-Lung Peng

  3. School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  4. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

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© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Athani, S., Joshi, S., Rao, B.A., Rai, S., Kini, N.G. (2021). Parallel Implementation of kNN Algorithm for Breast Cancer Detection. In: Bhateja, V., Peng, SL., Satapathy, S.C., Zhang, YD. (eds) Evolution in Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1176. Springer, Singapore. https://doi.org/10.1007/978-981-15-5788-0_46

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