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Hierarchical Implementation of Aggregate Functions

Most systems in HPC make use of hierarchical designs that allow multiple levels of parallelism to be exploited by programmers. The use of multiple multi-core/multi-processor computers to form a computer cluster supports both fine-grain and large-grain parallel computation. Aggregate function communications provide an easy to use and efficient set of mechanisms for communicating and coordinating between processing elements, but the model originally targeted only fine grain parallel hardware. This work shows that a hierarchical implementation of aggregate functions is a viable alternative to MPI (the standard Message Passing Interface library) for programming clusters that provide both fine grain and large grain execution. Performance of a prototype implementation is evaluated and compared to that of MPI.

Identiferoai:union.ndltd.org:uky.edu/oai:uknowledge.uky.edu:ece_etds-1116
Date01 January 2017
CreatorsQuevedo, Pablo
PublisherUKnowledge
Source SetsUniversity of Kentucky
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations--Electrical and Computer Engineering

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