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Author Liu, Ling
Source SpringerLink
Content type Text
Publisher SP Higher Education Press
File Format PDF
Copyright Year ©2013
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword big data ♦ cloud computing ♦ data analytics ♦ elastic scalability ♦ heterogeneous computing ♦ GPU ♦ PCM ♦ big data processing ♦ Computer Science
Abstract With computing systems undergone a fundamental transformation from single-processor devices at the turn of the century to the ubiquitous and networked devices and the warehouse-scale computing via the cloud, the parallelism has become ubiquitous at many levels. At micro level, parallelisms are being explored from the underlying circuits, to pipelining and instruction level parallelism on multi-cores or many cores on a chip as well as in a machine. From macro level, parallelisms are being promoted from multiple machines on a rack, many racks in a data center, to the globally shared infrastructure of the Internet. With the push of big data, we are entering a new era of parallel computing driven by novel and ground breaking research innovation on elastic parallelism and scalability. In this paper, we will give an overview of computing infrastructure for big data processing, focusing on architectural, storage and networking challenges of supporting big data paper. We will briefly discuss emerging computing infrastructure and technologies that are promising for improving data parallelism, task parallelism and encouraging vertical and horizontal computation parallelism.
ISSN 20952228
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2013-04-06
Publisher Institution Chinese Universities
Publisher Place Heidelberg
e-ISSN 20952236
Journal Frontiers of Computer Science in China
Volume Number 7
Issue Number 2
Page Count 6
Starting Page 165
Ending Page 170

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Source: SpringerLink