Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Hierarchical Parallelization of the Multilevel Fast Multipole Algorithm for the Efficient Solution of Large-Scale Scattering Problems
Date
2008-07-11
Author
Ergül, Özgür Salih
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
66
views
0
downloads
Cite This
URI
https://hdl.handle.net/11511/53374
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Hierarchical Parallelization of the Multilevel Fast Multipole Algorithm (MLFMA)
Gurel, Levent; Ergül, Özgür Salih (2013-02-01)
Due to its O(NlogN) complexity, the multilevel fast multipole algorithm (MLFMA) is one of the most prized algorithms of computational electromagnetics and certain other disciplines. Various implementations of this algorithm have been used for rigorous solutions of large-scale scattering, radiation, and miscellaneous other electromagnetics problems involving 3-D objects with arbitrary geometries. Parallelization of MLFMA is crucial for solving real-life problems discretized with hundreds of millions of unkno...
Hierarchical parallelisation strategy for multilevel fast multipole algorithm in computational electromagnetics
Ergül, Özgür Salih (Institution of Engineering and Technology (IET), 2008-01-03)
A hierarchical parallelisation of the multilevel fast multipole algorithm (MLFMA) for the efficient solution of large-scale problems in computational electromagnetics is presented. The tree structure of MLFMA is distributed among the processors by partitioning both the clusters and the samples of the fields appropriately for each level. The parallelisation efficiency is significantly improved compared to previous approaches, where only the clusters or only the fields are partitioned in a level.
Hierarchical multitasking control of discrete event systems: Computation of projections and maximal permissiveness
Schmidt, Klaus Verner; Cury, José E.r. (null; 2010-12-01)
This paper extends previous results on the hierarchical and decentralized control of multitasking discrete event systems (MTDES). Colored observers, a generalization of the observer property, together with local control consistency, allow to derive sufficient conditions for synthesizing modular and hierarchical control that are both strongly nonblocking (SNB) and maximally permissive. A polynomial procedure to verify if a projection fulfills the above properties is proposed and in the case they fail for a g...
Hierarchical coding of digital images for progressive transmission
Yalazan, Hakkı Tarkan; Yücel, Melek ; Department of Electrical and Electronics Engineering (1993)
Hierarchical distance learning by stacking nearest neighbor classifiers
Ozay, Mete; Yarman Vural, Fatoş Tunay (2016-05-01)
We propose a two-layer decision fusion technique, called Fuzzy Stacked Generalization (FSG) which establishes a hierarchical distance learning architecture. At the base-layer of an FSG, fuzzy k-NN classifiers receive different feature sets each of which is extracted from the same dataset to gain multiple views of the dataset At the meta-layer, first, a fusion space is constructed by aggregating decision spaces of all the base-layer classifiers. Then, a fuzzy k-NN classifier is trained in the fusion space by...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
Ö. S. Ergül, “Hierarchical Parallelization of the Multilevel Fast Multipole Algorithm for the Efficient Solution of Large-Scale Scattering Problems,” 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53374.