Paper Info
Title
A survey on graphic processing unit computing for large-scale data mining.
Abstract
General purpose computation using Graphic Processing Units (GPUs) is a well-established research area focusing on high-performance computing solutions for massively parallelizable and time-consuming problems. Classical methodologies in machine learning and data mining cannot handle processing of massive and high-speed volumes of information in the context of the big data era. GPUs have successfully improved the scalability of data mining algorithms to address significantly larger dataset sizes in many application areas. The popularization of distributed computing frameworks for big data mining opens up new opportunities for transformative solutions combining GPUs and distributed frameworks. This survey analyzes current trends in the use of GPU computing for large-scale data mining, discusses GPU architecture advantages for handling volume and velocity of data, identifies limitation factors hampering the scalability of the problems, and discusses open issues and future directions. (c) 2017 Wiley Periodicals, Inc.
Year
DOI
Venue
2018
10.1002/widm.1232
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY
Field
DocType
Volume
Data science,Data mining,Data stream mining,Transformative learning,CUDA,Computer science,Artificial intelligence,Computation,Architecture,General-purpose computing on graphics processing units,Big data,Machine learning,Scalability
Journal
8.0
Issue
ISSN
Citations 
1.0
1942-4787
7
PageRank 
References 
Authors
0.47
43
1
Name
Order
Citations
PageRank
Alberto Cano113011.20