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Home ยป Accelerating Complex Data Transfer for Cluster Computing
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Accelerating Complex Data Transfer for Cluster Computing

Authors: 

Alexey Khrabrov and Eyal de Lara, University of Toronto

Abstract: 

The ability to move data quickly between the nodes of a distributed system is important for the performance of cluster computing frameworks, such as Hadoop and Spark. We show that in a cluster with modern networking technology data serialization is the main bottleneck and source of overhead in the transfer of rich data in systems based on high-level programming languages such as Java. We propose a new data transfer mechanism that avoids serialization altogether by using a shared clusterwide address space to store data. The design and a prototype implementation of this approach are described. We show that our mechanism is significantly faster than serialized data transfer, and propose a number of possible applications for it.

Alexey Khrabrov, University of Toronto

Eyal de Lara, University of Toronto

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BibTeX
@inproceedings {196324,
author = {Alexey Khrabrov and Eyal de Lara},
title = {Accelerating Complex Data Transfer for Cluster Computing},
booktitle = {8th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 16)},
year = {2016},
address = {Denver, CO},
url = {https://www.usenix.org/conference/hotcloud16/workshop-program/presentation/khrabrov},
publisher = {USENIX Association},
month = jun,
}
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