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Cooperative Software-hardware Acceleration of K-means on a Tightly Coupled CPU-FPGA System

Author:

Tarek S. AbdelrahmanAuthors Info & Claims

ACM Transactions on Architecture and Code Optimization (TACO), Volume 17, Issue 3

Article No.: 20, Pages 1 - 24

https://doi.org/10.1145/3406114

Published: 17 August 2020 Publication History

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Abstract

We consider software-hardware acceleration of K-means clustering on the Intel Xeon+FPGA platform. We design a pipelined accelerator for K-means and combine it with CPU threads to assess performance benefits of (1) acceleration when data are only accessed from system memory and (2) cooperative CPU-FPGA acceleration. Our evaluation shows that the accelerator is up to 12.7×/2.4× faster than a single CPU thread for the assignment/update step of K-means. The cooperative use of threads and FPGA is roughly 1.9× faster than CPU threads alone or the FPGA by itself. Our approach delivers 4×–5× higher throughput compared to existing offload processing approaches.

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Cited By

Shirke SJayakumar NPatil S(2024)Design and performance analysis of modern computational storage devices: A systematic reviewExpert Systems with Applications10.1016/j.eswa.2024.123570250(123570)Online publication date: Sep-2024
https://doi.org/10.1016/j.eswa.2024.123570
Du ZZhang QLin MLi SLi XJu L(2023)A Comprehensive Memory Management Framework for CPU-FPGA Heterogenous SoCsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2022.317932342:4(1058-1071)Online publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1109/TCAD.2022.3179323
Harkishanka APrakash AGupta NMohammad AAsati A(2023)Hardware Software Co-design of k-means Clustering Algorithm2023 9th International Conference on Signal Processing and Communication (ICSC)10.1109/ICSC60394.2023.10441233(688-693)Online publication date: 21-Dec-2023
https://doi.org/10.1109/ICSC60394.2023.10441233
Show More Cited By

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Cooperative Software-hardware Acceleration of K-means on a Tightly Coupled CPU-FPGA System

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Published In

cover image ACM Transactions on Architecture and Code Optimization

ACM Transactions on Architecture and Code Optimization Volume 17, Issue 3

September 2020

200 pages

ISSN:1544-3566

EISSN:1544-3973

DOI:10.1145/3415154

Editor:
David Kaeli
Northeastern University, USA

Issue’s Table of Contents

Copyright © 2020 ACM.

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Association for Computing Machinery

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Publication History

Published: 17 August 2020

Accepted: 01 June 2020

Revised: 01 March 2020

Received: 01 February 2020

Published in TACO Volume 17, Issue 3

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Cited By

Shirke SJayakumar NPatil S(2024)Design and performance analysis of modern computational storage devices: A systematic reviewExpert Systems with Applications10.1016/j.eswa.2024.123570250(123570)Online publication date: Sep-2024
https://doi.org/10.1016/j.eswa.2024.123570
Du ZZhang QLin MLi SLi XJu L(2023)A Comprehensive Memory Management Framework for CPU-FPGA Heterogenous SoCsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2022.317932342:4(1058-1071)Online publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1109/TCAD.2022.3179323
Harkishanka APrakash AGupta NMohammad AAsati A(2023)Hardware Software Co-design of k-means Clustering Algorithm2023 9th International Conference on Signal Processing and Communication (ICSC)10.1109/ICSC60394.2023.10441233(688-693)Online publication date: 21-Dec-2023
https://doi.org/10.1109/ICSC60394.2023.10441233
Wan LZheng WYuan X(2021)HCE: A Runtime System for Efficiently Supporting Heterogeneous Cooperative ExecutionIEEE Access10.1109/ACCESS.2021.31248569(147264-147279)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3124856
Huang ZYang XMin JWang HWei P(2021)Collision detection algorithm on abrasive belt grinding blisk based on improved octree segmentationThe International Journal of Advanced Manufacturing Technology10.1007/s00170-021-08213-w118:11-12(4105-4121)Online publication date: 22-Oct-2021
https://doi.org/10.1007/s00170-021-08213-w

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