A Parallel Algorithm for the Solution of the Deconvolution Problem in Heterogeneous Networks

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Title: A Parallel Algorithm for the Solution of the Deconvolution Problem in Heterogeneous Networks
Authors: Alonso, PedroLastovetsky, AlexeyVidal, Antonio M.
Permanent link: http://hdl.handle.net/10197/12354
Date: 19-Dec-2005
Online since: 2021-07-28T15:29:26Z
Abstract: In this work we present two parallel algorithms for the solution of a given least squares problem with structured matrices. This problem arises in many applications most related to digital signal processing, an example is given. Both parallel algorithms have been designed to speed–up the sequential one in a heterogeneous network of computers. They differ from the approximation followed to implement parallel algorithms on heterogeneous networks of computers known as HeHo and HoHe strategies. However, our study goes beyond the practical usefulness of our heterogeneous parallel application. One one hand, the results obtained validates the recent developed HeteroMPI as a very useful tool for programming heterogeneous parallel algorithms. On the other hand, although HeteroMPI has initially been designed to apply the HeHo strategy, we propose a way this tool can be used in the HoHe strategy. Pros and cons of the use of HeteroMPI for both strategies will be deeply study through the application example.
Funding Details: Spanish Government
Type of material: Technical Report
Publisher: University College Dublin. School of Computer Science and Informatics
Series/Report no.: UCD CSI Technical Reports; ucd-csi-2006-2
Copyright (published version): 2005 the Authors
Keywords: Sequential algorithmsParallel algorithmsHeHo strategyHoHe strategy
Other versions: https://web.archive.org/web/20080226040105/http:/csiweb.ucd.ie/Research/TechnicalReports.html
Language: en
Status of Item: Not peer reviewed
This item is made available under a Creative Commons License: https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Appears in Collections:Computer Science and Informatics Technical Reports

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