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Erschienen in:
An Overview of Issues and Recent Developments in Cloud Computing and Storage Security Kapitel lesen Erstes Kapitel lesen

2014 | OriginalPaper | Buchkapitel

GPGPU Computing for Cloud Auditing

verfasst von : Virginia W. Ross, Miriam E. Leeser

Erschienen in: High Performance Cloud Auditing and Applications

Verlag: Springer New York

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Abstract

With the increasing computational complexity of cloud auditing and other data-intensive analysis applications, there is a growing need for computing platforms that can handle massive data sets and perform rapid analysis. These needs are met by systems with accelerators, such as Graphics Processing Units (GPUs), that can perform data analysis with a high level of parallelism employing tools like Hadoop MapReduce to handle massively parallel computing jobs. Applying GPUs to general purpose processing is known as GPGPU. This chapter uses an introductory approach to cover the basics of GPUs and GPGPU computing and their application to cloud computing and handling of large data sets. The main aim is to give the reader a broad background on how GPGPUs are used and their contribution to advances in cloud auditing.

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Vorheriges Kapitel Assured Information Sharing (AIS)Using Private Clouds
Nächstes Kapitel CPU-GPU System Designs for High Performance Cloud Computing
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Metadaten
Titel
GPGPU Computing for Cloud Auditing
verfasst von
Virginia W. Ross
Miriam E. Leeser
Copyright-Jahr
2014
Verlag
Springer New York
Buch
High Performance Cloud Auditing and Applications

Print ISBN: 978-1-4614-3295-1

Electronic ISBN: 978-1-4614-3296-8

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-1-4614-3296-8_10

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