GPU-Accelerated Cloud Computing for Data-Intensive Applications

Naga K. Govindaraju; Bingsheng He; Jianlong Zhong; Wenbin Fang; Qiong Luo

doi:10.1007/978-1-4939-1905-5_5

GPU-Accelerated Cloud Computing for Data-Intensive Applications

Naga K. Govindaraju, Bingsheng He, Jianlong Zhong, Wenbin Fang, Qiong Luo^*

^*Corresponding author for this work

Department of Computer Science and Engineering

Research output: Chapter in Book/Conference Proceeding/Report › Book Chapter › peer-review

Abstract

Recently, many large-scale data-intensive applications have emerged from the Internet and science domains. They pose significant challenges on the performance, scalability and programmability of existing data management systems. The challenges are even greater when these data management systems run on emerging parallel and distributed hardware and software platforms. In this chapter, we study the use of the GPU (Graphics Processing Units) in MapReduce and general graph processing in the Cloud for these data-intensive applications. In particular, we report our experiences in developing system prototypes, and discuss the open problems in the interplay between data-intensive applications and system platforms.

Original language	English
Title of host publication	Cloud Computing for Data-Intensive Applications
Publisher	Springer
Pages	105-129
ISBN (Print)	9781493919048, 9781493919055
DOIs	https://doi.org/10.1007/978-1-4939-1905-5_5
Publication status	Published - Jan 2014

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10.1007/978-1-4939-1905-5_5

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GPU-Accelerated Cloud Computing for Data-Intensive Applications

Abstract

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