NDLI: Speeding up K-Means Algorithm by GPUs

Content Provider	IEEE Xplore Digital Library
Author	You Li Kaiyong Zhao Xiaowen Chu Jiming Liu
Copyright Year	2010
Abstract	Cluster analysis plays a critical role in a wide variety of applications, but it is now facing the computational challenge due to the continuously increasing data volume. Parallel computing is one of the most promising solutions to overcoming the computational challenge. In this paper, we target at parallelizing k-Means, which is one of the most popular clustering algorithms, by using the widely available Graphics Processing Units (GPUs). Different from existing GPU-based k-Means algorithms, we observe that data dimension is an important factor that should be taken into consideration when parallelizing k-Means on GPUs. In particular, we use two different strategies for low-dimensional data sets and high-dimensional data sets respectively, in order to make the best use of the power of GPUs. For low-dimensional data sets, we exploit GPU on-chip registers to significantly decrease data access latency. For high-dimensional data sets, we design a novel algorithm which simulates matrix multiplication and exploits GPU on-chip registers and also on-chip shared memory to achieve high compute-to-memory-access ratio. As a result, our GPU-based k-Means algorithm is three to eight times faster than the best reported GPU-based algorithm.
Starting Page	115
Ending Page	122
File Size	511996
Page Count	8
File Format	PDF
ISBN	9781424475476
e-ISBN	9781424475483
DOI	10.1109/CIT.2010.60
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-29
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis CUDA cluster Instruction sets Memory management Clustering algorithms k-means Registers System-on-a-chip GPGPU Graphics processing unit
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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