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End-to-end dataflow parallelism for transfer throughput optimization

  • Louisiana State University

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

Abstract

The emerging petascale increase in the data produced by large-scale scientific applications necessitates innovative solutions for efficient transfer of data through the advanced infrastructure provided by today's high-speed networks and complex computer-architectures (e.g. supercomputers, parallel storage systems). Although the current optical networking technology reached transport speeds of 100Gbps, the applications still suffer from the inadequate transport protocols and end-system bottlenecks such as processor speed, disk I/O speed and network interface card limits that cause underutilization of the existing network infrastructure and let the application achieve only a small portion of the theoretical performance. Fortunately, with the parallelism provided by usage of multiple CPUs/nodes and multiple disks present in today's systems, these bottlenecks could be eliminated. However it is necessary to understand the characteristics of the end-systems and the transport protocol used. In this book chapter, we analyze methodologies that will improve the data transfer speed of applications and provide maximal speeds that could be obtained from the available end-system resources and high-speed networks through usage of end-to-end dataflow parallelism.

Original languageEnglish
Title of host publicationAdvancements in Distributed Computing and Internet Technologies
Subtitle of host publicationTrends and Issues
PublisherIGI Global
Pages23-39
Number of pages17
ISBN (Print)9781613501108
DOIs
StatePublished - 2011

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