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Towards a scalable parallel MLFMA in three dimensions

Bart Michiels, Jan Fostier, Ignace Bogaert, Piet Demeester, Daniel De Zutter
2011 CEM'11 Computational Electromagnetics International Workshop  
The development of a scalable parallel Multilevel Fast Multipole Algorithm (MLFMA) for three dimensional electromagnetic scattering problems is reported.  ...  Crucial to ensure the scalability of the algorithm, is that the radiation patternssampled on the sphere-are partitioned in two dimensions, i.e. both in azimuth and elevation directions.  ...  For the lower levels, k-space partitioning can not provide for a balanced load division. For the same reason as for spatial partitioning, k-space partitioning allows for only P = O(1) processes.  ... 
doi:10.1109/cem.2011.6047346 fatcat:hdx7rv26bjazna7ujnyklztq3y

Scalable video summarization of cultural video documents in cross-media space based on data cube approach

Karina R. Perez-Daniel, Mariko Nakano Miyatake, Jenny Benois-Pineau, Sofian Maabout, Gabriel Sargent
2014 2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI)  
This paper proposes a scalable video summarization approach which provides multiple views and levels of details. Our method relies on the usage of cross media space and consensus clustering method.  ...  The method is designed for weakly structured content such as cultural documentaries and was tested on the INA corpus of cultural archives.  ...  Elie Génard for his efficient help in conducting computational experiments.  ... 
doi:10.1109/cbmi.2014.6849824 dblp:conf/cbmi/Perez-DanielNBMS14 fatcat:nvn7e226szdjlma2if7ejfgceq

Space-time balancing domain decomposition [article]

Santiago Badia, Marc Olm
2017 arXiv   pre-print
Excellent wall clock time weak scalability is achieved for space-time parallel solvers on some thousands of cores.  ...  In this work, we propose two-level space-time domain decomposition preconditioners for parabolic problems discretized using finite elements.  ...  We denote the k-th element by δ k . = (t k−1 , t k ], for k = 1, . . . , K. Space-time discretization.  ... 
arXiv:1701.03477v1 fatcat:x7h2tlcstrgpnf33eg4zm4slty

Scalable Varied Density Clustering Algorithm for Large Datasets

Ahmed Fahim, Abd-Elbadeeh Salem, Fawzy Torkey, Mohamed Ramadan, Gunter Saake
2010 Journal of Software Engineering and Applications  
We achieved the scalability of the proposed algorithm by using the k-means algorithm to get initial partition of the dataset, applying the enhanced DBSCAN on each partition, and then using a merging process  ...  This means the proposed algorithm consists of three stages.  ...  Figure 1 . 1 Main stages of the scalable EDBSCAN Figure 2 . 2 Initial partition resulted from k-means algorithm ure 3.  ... 
doi:10.4236/jsea.2010.36069 fatcat:yeahdlee45g67n7mfmd6vqub7m

Space-Time Balancing Domain Decomposition

Santiago Badia, Marc Olm
2017 SIAM Journal on Scientific Computing  
We use classical functional analysis notation for Sobolev spaces. Domain partitions.  ...  M denotes mass matrix operators related to the time derivative discretization, K is used for the rest of the terms in the PDE operator, and A is used for the sum of these two operators.  ...  For the time interval (0, T ], we define a time partition {0 = t 0 , t 1 , . . . , t K = T } into K time elements. We denote the kth element by δ k . = (t k−1 , t k ] for k = 1, . . . , K.  ... 
doi:10.1137/16m1074266 fatcat:xdvbrkwwobcytmerise3qyvnsm

Performing large full-wave simulations by means of a parallel MLFMA implementation

B. Michiels, J. Fostier, I. Bogaert, D. De Zutter
2013 2013 IEEE Antennas and Propagation Society International Symposium (APSURSI)  
The data structures of the MLFMAtree are partitioned according to the so-called hierarchical partitioning scheme, while the radiation patterns are partitioned in a blockwise way.  ...  transition from spatial to k-space partitioning, which can lead to a scalable partitioning scheme [1] , [2] .  ...  One MLFMA-level before the transition from spatial to k-space, the O( √ N ) boxes have to be partitioned among O(N ) CPU-cores.  ... 
doi:10.1109/aps.2013.6711598 fatcat:uhznxf3oznflvm6kitx2ec7eie

On the Scalability of Evidence Accumulation Clustering

Andre Lourenco, Ana L.N. Fred, Anil K. Jain
2010 2010 20th International Conference on Pattern Recognition  
This work focuses on the scalability of the Evidence Accumulation Clustering (EAC) method. We first address the space complexity of the co-association matrix.  ...  Using a split and merge strategy combined with a sparse matrix representation, we empirically show that a linear space complexity is achievable in this framework, leading to the scalability of EAC method  ...  For the sake of simplicity, in the next section we illustrate and evaluate this strategy using K-means clusterings for constructing the ensemble. IV.  ... 
doi:10.1109/icpr.2010.197 dblp:conf/icpr/LourencoFJ10 fatcat:jshwlfioo5b45jvcmxv5ojsm3q

Balanced k-means for Parallel Geometric Partitioning [article]

Moritz von Looz, Charilaos Tzovas, Henning Meyerhenke
2018 arXiv   pre-print
In this paper, we present a scalable version of k-means that is adapted to yield balanced clusters. Balanced k-means constitutes the core of our new partitioning algorithm Geographer.  ...  Bootstrapping of initial centers is performed with space-filling curves, leading to fast convergence of the subsequent balanced k-means algorithm.  ...  We thank Michael Axtmann for providing us with a preliminary implementation of his scalable sorting algorithm.  ... 
arXiv:1805.01208v1 fatcat:d33hxupu5rgp7jj2mxdndfktu4

Page 1070 of The Journal of the Operational Research Society Vol. 60, Issue 8 [page]

2009 The Journal of the Operational Research Society  
Improved scalable versions of partitioning methods, such as k-means and k-medoids, have also been developed.  ...  Examples of the partitioning approach are the classic k-means and k-medoids clustering algorithms. Both of these methods can be considered greedy heuristics.  ... 

Scalable and Fast Top-k Most Similar Trajectories Search Using MapReduce In-Memory [chapter]

Douglas Alves Peixoto, Nguyen Quoc Viet Hung
2016 Lecture Notes in Computer Science  
In addition, we propose a spatialtemporal index for our partitions to efficiently prune the search space, improve system throughput and scalability.  ...  We propose a space/time data partitioning based on Voronoi diagrams and time pages, named Voronoi Pages, in order to provide both spatial-temporal data organization and process decentralization.  ...  This research is partially supported by the Brazilian National Council for Scientific and Technological Development (CNPq).  ... 
doi:10.1007/978-3-319-46922-5_18 fatcat:uq2dduh3ene2lpj6wwi33wkqqy

Optimized combinatorial clustering for stochastic processes

Jumi Kim, Wookey Lee, Justin Jongsu Song, Soo-Bok Lee
2017 Cluster Computing  
In this paper, we suggest an optimized combinatorial clustering algorithm for noisy performance which is essential for large data with random sampling.  ...  The algorithm outperforms conventional approaches through various numerical and qualitative thresholds like mean and standard deviation of accuracy and computation speed.  ...  Such as k-means and k-medoids, improved scalable versions of partitioning methods.  ... 
doi:10.1007/s10586-017-0763-1 fatcat:tgpierpyybdu5cuwes6qctn5oy

A scalable association rule learning heuristic for large datasets

Haosong Li, Phillip C.-Y. Sheu
2021 Journal of Big Data  
However, most of these algorithms suffer from the problem of scalability either because of tremendous time complexity or memory usage, especially when the dataset is large and the minimum support (minsup  ...  The space complexity of this is O(k) = O(1), where k is the number of partitions.  ...  If the modified Apriori algorithm is selected, the theoretical space complexity for each partition is O 2 ) space comparing to the Apriori algorithm.  ... 
doi:10.1186/s40537-021-00473-3 fatcat:ozhotg54jfbkdburkrtyfgnjuu

A comprehensive comparison study of document clustering for a biomedical digital library MEDLINE

Illhoi Yoo, Xiaohua Hu
2006 Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries - JCDL '06  
, K-means, and Suffix Tree Clustering in terms of the efficiency, the effectiveness, and the scalability.  ...  In this paper, we perform a comprehensive comparison study of various document clustering approaches such as three hierarchical methods (single-link, complete-link, and complete link), Bisecting K-means  ...  Table 8 . 8 Comparison of Evaluation Metrics and Running Times for STC and Partitional algorithms on the smallest twenty four datasets (due to the scalability problem of STC) Bisecting K-means Type A  ... 
doi:10.1145/1141753.1141802 dblp:conf/jcdl/YooH06 fatcat:tidbbq52ojculi74afzwdns4gy

Scalable Clustering Algorithms for Big data: A Review

Mahmoud A. Mahdi, Khalid M. Hosny, Ibrahim Elhenawy
2021 IEEE Access  
The key idea of the paper is to highlight the main advantages and disadvantages of clustering algorithms for dealing with big data in a scalable approach behind the different other features.  ...  In this paper, we review the most relevant clustering algorithms in a categorized manner, provide a comparison of clustering methods for large-scale data and explain the overall challenges based on clustering  ...  K-means [22] , and K-medoids [23] are most famous algorithms based on partitioning. K-means iterative update the centre of the cluster until coverage data.  ... 
doi:10.1109/access.2021.3084057 fatcat:wwjmq557fbbfjgr4w3makbjkg4

Multiobjective hBOA, clustering, and scalability

Martin Pelikan, Kumara Sastry, David E. Goldberg
2005 Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05  
It is first argued that for good scalability, clustering or some other form of niching in the objective space is necessary and the size of each niche should be approximately equal.  ...  This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominated sorting genetic algorithm  ...  Government is authorized to reproduce and distribute reprints for government purposes notwithstanding any copyright notation thereon.  ... 
doi:10.1145/1068009.1068122 dblp:conf/gecco/PelikanSG05 fatcat:pmfsfargbnaifm2p3dlqiganuu
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