Welcome to the InfoSci Platform
Reference Hub1
End-to-End Dataflow Parallelism for Transfer Throughput Optimization

End-to-End Dataflow Parallelism for Transfer Throughput Optimization

Esma Yildirim, Tevfik Kosar
Copyright: © 2012 |Pages: 17
ISBN13: 9781613501108|ISBN10: 1613501102|EISBN13: 9781613501115
DOI: 10.4018/978-1-61350-110-8.ch002
Cite Chapter Cite Chapter

MLA

Yildirim, Esma, and Tevfik Kosar. "End-to-End Dataflow Parallelism for Transfer Throughput Optimization." Advancements in Distributed Computing and Internet Technologies: Trends and Issues, edited by Al-Sakib Khan Pathan, et al., IGI Global, 2012, pp. 23-39. https://doi.org/10.4018/978-1-61350-110-8.ch002

APA

Yildirim, E. & Kosar, T. (2012). End-to-End Dataflow Parallelism for Transfer Throughput Optimization. In A. Pathan, M. Pathan, & H. Lee (Eds.), Advancements in Distributed Computing and Internet Technologies: Trends and Issues (pp. 23-39). IGI Global. https://doi.org/10.4018/978-1-61350-110-8.ch002

Chicago

Yildirim, Esma, and Tevfik Kosar. "End-to-End Dataflow Parallelism for Transfer Throughput Optimization." In Advancements in Distributed Computing and Internet Technologies: Trends and Issues, edited by Al-Sakib Khan Pathan, Mukaddim Pathan, and Hae Young Lee, 23-39. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-61350-110-8.ch002

Export Reference

Mendeley
Favorite

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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.