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Relevant bibliographies by topics / Multiplication de matrices creuses

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Academic literature on the topic 'Multiplication de matrices creuses'

Author: Grafiati

Published: 16 November 2024

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Journal articles on the topic "Multiplication de matrices creuses"

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Keles, Hasan. "Multiplication of Matrices." Indonesian Journal of Mathematics and Applications 2, no. 1 (2024): 1–8. http://dx.doi.org/10.21776/ub.ijma.2024.002.01.1.

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This study is about multiplication of matrices. Multiplication of real numbers, which can be written along a line, is also two way. Here, the direction is not an influential factor even when the elements are switched. For example $3.2=6$ and $2.3=6. $ In matrices this makes left and right multiplication is mandatory. Left multiplication is already defined. This is multiplication in known matrices. Left multiplication is used in the studies since the definition of this operation until today. The most insurmountable situation here is that matrices do not commutative Property according to this op

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Roesler, Friedrich. "Generalized Matrices." Canadian Journal of Mathematics 41, no. 3 (1989): 556–76. http://dx.doi.org/10.4153/cjm-1989-024-5.

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Similar to the multiplication of square matrices one can define multiplications for three dimensional matrices, i.e., for the "cubes" of the vector spacewhere I denotes a finite set of indices and Kis any field. The multiplications shall imitate the matrix multiplication: To obtain the coefficient γxyzof the product (γxyz) — (αxyz)( βxyz),all coefficients axij, ij∈ I, of the horizontal plane with index xof (αxyz)are multiplied with certain coefficients βhgzof the vertical plane with index z of (βxyz)and the results are added:

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Bair, J. "72.34 Multiplication by Diagonal Matrices." Mathematical Gazette 72, no. 461 (1988): 228. http://dx.doi.org/10.2307/3618262.

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Sowa, Artur. "Factorizing matrices by Dirichlet multiplication." Linear Algebra and its Applications 438, no. 5 (2013): 2385–93. http://dx.doi.org/10.1016/j.laa.2012.09.021.

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Councilman, Samuel. "Sharing Teaching Ideas: Bisymmetric Matrices: Some Elementary New Problems." Mathematics Teacher 82, no. 8 (1989): 622–23. http://dx.doi.org/10.5951/mt.82.8.0622.

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In introductory linear algebra courses one continually seeks interesting sets of matrices that are closed under the operations of matrix addition, scalar multiplication, and if possible, matrix multiplication. Most texts mention symmetric and antisymmetric matrices and ask the reader to show that these sets are closed under matrix addition and scalar multiplication but fail to be closed under matrix multiplication. Few textbooks, if any, suggest an investigation of the set of matrices that are symmetric with respect to both diagonals, namely bisymmetric matrices. The following is a sequence of

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Ignatenko, M. V., and L. A. Yanovich. "On the theory of interpolation of functions on sets of matrices with the Hadamard multiplication." Proceedings of the National Academy of Sciences of Belarus. Physics and Mathematics Series 58, no. 3 (2022): 263–79. http://dx.doi.org/10.29235/1561-2430-2022-58-3-263-279.

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This article is devoted to the problem of interpolation of functions defined on sets of matrices with multiplication in the sense of Hadamard and is mainly an overview. It contains some known information about the Hadamard matrix multiplication and its properties. For functions defined on sets of square and rectangular matrices, various interpolation polynomials of the Lagrange type, containing both the operation of matrix multiplication in the Hadamard sense and the usual matrix product, are given. In the case of analytic functions defined on sets of square matrices with the Hadamard multipli

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Abobala, Mohammad. "On Refined Neutrosophic Matrices and Their Application in Refined Neutrosophic Algebraic Equations." Journal of Mathematics 2021 (February 13, 2021): 1–5. http://dx.doi.org/10.1155/2021/5531093.

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The objective of this paper is to introduce the concept of refined neutrosophic matrices as matrices such as multiplication, addition, and ring property. Also, it determines the necessary and sufficient condition for the invertibility of these matrices with respect to multiplication. On the contrary, nilpotency and idempotency properties will be discussed.

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Waterhouse, William C. "Circulant-style matrices closed under multiplication." Linear and Multilinear Algebra 18, no. 3 (1985): 197–206. http://dx.doi.org/10.1080/03081088508817686.

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Theeracheep, Siraphob, and Jaruloj Chongstitvatana. "Multiplication of medium-density matrices using TensorFlow on multicore CPUs." Tehnički glasnik 13, no. 4 (2019): 286–90. http://dx.doi.org/10.31803/tg-20191104183930.

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Matrix multiplication is an essential part of many applications, such as linear algebra, image processing and machine learning. One platform used in such applications is TensorFlow, which is a machine learning library whose structure is based on dataflow programming paradigm. In this work, a method for multiplication of medium-density matrices on multicore CPUs using TensorFlow platform is proposed. This method, called tbt_matmul, utilizes TensorFlow built-in methods tf.matmul and tf.sparse_matmul. By partitioning each input matrix into four smaller sub-matrices, called tiles, and applying an

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Mangngiri, Itsar, Qonita Qurrota A’yun, and Wasono Wasono. "AN ORDER-P TENSOR MULTIPLICATION WITH CIRCULANT STRUCTURE." BAREKENG: Jurnal Ilmu Matematika dan Terapan 17, no. 4 (2023): 2293–304. http://dx.doi.org/10.30598/barekengvol17iss4pp2293-2304.

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Research on mathematical operations involving multidimensional arrays or tensors has increased along with the growing applications involving multidimensional data analysis. The -product of order- tensor is one of tensor multiplications. The -product is defined using two operations that transform the multiplication of two tensors into the multiplication of two block matrices, then the result is a block matrix which is further transformed back into a tensor. The composition of both operations used in the definition of -product can transform a tensor into a block circulant matrix. This research d

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Dissertations / Theses on the topic "Multiplication de matrices creuses"

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Gonon, Antoine. "Harnessing symmetries for modern deep learning challenges : a path-lifting perspective." Electronic Thesis or Diss., Lyon, École normale supérieure, 2024. http://www.theses.fr/2024ENSL0043.

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Les réseaux de neurones connaissent un grand succès pratique, mais les outils théoriques pour les analyser sont encore souvent limités à des situations simples qui ne reflètent pas toute la complexité des cas pratiques d'intérêts. Cette thèse vise à réduire cet écart en rendant les outils théoriques plus concrets. Le premier axe de recherche concerne la généralisation : un réseau donné pourra-t-il bien se comporter sur des données jamais vues auparavant ? Ce travail améliore les garanties de généralisation basées sur la norme de chemins, les rendant applicables à des réseaux ReLU incluant du p

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Lawson, Jean-Christophe. "Smart : un neurocalculateur parallèle exploitant des matrices creuses." Grenoble INPG, 1993. http://www.theses.fr/1993INPG0030.

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Les annees 80 montrerent l'eclosion du paradigme neuromimetique qui sommeillait depuis un demi-siecle. La simulation interactive intensive est un element cle pour des progres de cette approche qui fait generalement appel a des systemes non lineaires de grande taille. Ainsi, la faible efficacite des calculateurs est un element qui ralentit le developpement de nouveaux modeles. Bien que les modeles existant fassent apparaitre des comportements prometteurs, le fosse separant ces modeles des architectures nerveuses reste abyssal. L'analyse des principales caracteristiques nerveuses et leur traduct

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Geronimi, Sylvain. "Determination d'ensembles essentiels minimaux dans les matrices creuses : application a l'analyse des circuits." Toulouse 3, 1987. http://www.theses.fr/1987TOU30104.

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Vömel, Christof. "Contributions à la recherche en calcul scientifique haute performance pour les matrices creuses." Toulouse, INPT, 2003. http://www.theses.fr/2003INPT003H.

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Nous nous intéressons au développement d'un nouvel algorithme pour estimer la norme d'une matrice de manière incrémentale, à l'implantation d'un modèle de référence des Basic Linear Algebra Subprograms for sparse matrices (Sparse BLAS), et à la réalisation d'un nouveau gestionnaire de tâches pour MUMPS, un solveur multifrontal pour des architectures à mémoire distribuée. Notre méthode pour estimer la norme d'une matrice s'applique aux matrices denses et creuses. Elle peut s'avérer utile dans le cadre des factorisations QR, Cholesky, ou LU. Le standard Sparse BLAS définit des interfaces génériq

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Grigori, Laura. "Prédiction de structure et algorithmique parallèle pour la factorisation LU des matrices creuses." Nancy 1, 2001. http://www.theses.fr/2001NAN10264.

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Cette thèse traite du calcul numérique parallèle et les résultats de recherche portent sur la factorisation LU, telle qu'elle est utilisée pour résoudre des systèmes linéaires creux non-symétriques. En général, les calculs sur des matrices creuses ont une phase initiale de prédiction structurelle de la sortie, qui permet l'allocation de la mémoire, l'initialisation des structures de données et l'ordonnancement des tâches en parallèle. Dans ce but, nous étudions la prédiction structurelle pour la factorisation LU avec pivotage partiel. Nous nous intéressons principalement à identifier des limit

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Geronimi, Sylvain. "Détermination d'ensembles essentiels minimaux dans les matrices creuses application à l'analyse des circuits /." Grenoble 2 : ANRT, 1987. http://catalogue.bnf.fr/ark:/12148/cb376053608.

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Puglisi, Chiara. "Factorisation QR de grandes matrices creuses basée sur une méthode multifrontale dans un environnement multiprocesseur." Toulouse, INPT, 1993. http://www.theses.fr/1993INPT091H.

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Nous nous interessons a la factorisation qr de grandes matrices creuses carrees et sur-determinees dans un environnement mimd a memoire partagee. Nous supposons que le rang des vecteurs colonnes de ces matrices est maximal. Notre demarche est basee sur la methode multifrontale (duff et reid (1983)) et utilise les transformations de householder. Nous donnons une description detaillee de l'approche multifrontale pour la factorisation qr et de son implementation dans un environnement multiprocesseur. Nous montrons qu'en choisissant de facon adequate la strategie de factorisation de nuds, des gain

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EDJLALI, GUY. "Contribution a la parallelisation de methodes iteratives hybrides pour matrices creuses sur architectures heterogenes." Paris 6, 1994. http://www.theses.fr/1994PA066360.

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Cette these traite de programmation parallele heterogene, des structures de donnees irregulieres et de methode iterative hybride. La methode iterative choisie est la methode d'arnoldi de calcul de valeurs propres et de vecteurs propres de matrices creuses. Dans une premiere partie, une implementation data-parallele de cette methode a ete realisee. Cela a permis de mettre en evidence le comportement du programme et les lacunes existantes au niveau des outils de manipulation de matrices creuses. Dans une deuxieme partie, nous avons developpe des outils de manipulation de matrices creuses et prop

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Brown, Christopher Ian. "A VLSI device for multiplication of high order sparse matrices." Thesis, University of Sheffield, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.265915.

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Guermouche, Abdou. "Étude et optimisation du comportement mémoire dans les méthodes parallèles de factorisation de matrices creuses." Lyon, École normale supérieure (sciences), 2004. http://www.theses.fr/2004ENSL0284.

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Les méthodes directes de résolution de systèmes linéaires creux sont connues pour leurs besoins mémoire importants qui peuvent constituer une barrière au traitement de problèmes de grandes taille. De ce fait, les travaux effectués durant cette thèse ont porté d'une part sur l'étude du comportement mémoire d'un algorithme de factorisation de matrices creuses, en l'occurrence la méthode multifrontale, et d'autre part sur l'optimisation et la minimisation de la mémoire nécessaire au bon déroulement de la factorisation aussi bien dans un cadre séquentiel que parallèle. Ainsi, des algorithmes optim

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Books on the topic "Multiplication de matrices creuses"

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United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., ed. An efficient sparse matrix multiplication scheme for the CYBER 205 computer. National Aeronautics and Space Administration, Scientific and Technical Information Division, 1988.

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Munerman, Viktor, Vadim Borisov, and Aleksandra Kononova. Mass data processing. Algebraic models and methods. INFRA-M Academic Publishing LLC., 2023. http://dx.doi.org/10.12737/1906037.

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The monograph is devoted to mathematical and algorithmic support of mass data processing based on algebraic models. One of the most common classes of mass processing is considered - processing of highly active structured data. The construction of algebraic models of data and calculations and methods of proving their correspondence are analyzed. Three algebraic systems are studied, which can be used both as data models and as models of calculations. The algebraic and axiomatic methods of proving the correspondence of these models are investigated. A proof of their correspondence is given: homom

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Gohberg, Israel, Yuli Eidelman, and Iulian Haimovici. Separable Type Representations of Matrices and Fast Algorithms: Volume 1 Basics. Completion Problems. Multiplication and Inversion Algorithms. Birkhauser Verlag, 2013.

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Mann, Peter. The (Not So?) Basics. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198822370.003.0030.

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This chapter discusses matrices. Matrices appear in many instances across physics, and it is in this chapter that the background necessary for understanding how to use them in calculations is provided. Although matrices can be a little daunting upon first exposure, they are very handy for a lot of classical physics. This chapter reviews the basics of matrices and their operations. It discusses square matrices, adjoint matrices, cofactor matrices and skew-symmetric matrices. The concepts of matrix multiplication, transpose, inverse, diagonal, identity, Pfaffian and determinant are examined. The

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Book chapters on the topic "Multiplication de matrices creuses"

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Eidelman, Yuli, Israel Gohberg, and Iulian Haimovici. "Multiplication of Matrices." In Separable Type Representations of Matrices and Fast Algorithms. Springer Basel, 2013. http://dx.doi.org/10.1007/978-3-0348-0606-0_17.

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Josipović, Miroslav. "Geometric Algebra and Matrices." In Geometric Multiplication of Vectors. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-01756-9_4.

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Russo, Luís M. S. "Multiplication Algorithms for Monge Matrices." In String Processing and Information Retrieval. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16321-0_9.

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Tiskin, A. "Bulk-synchronous parallel multiplication of boolean matrices." In Automata, Languages and Programming. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0055078.

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Tiskin, A. "Erratum: Bulk-Synchronous Parallel Multiplication of Boolean Matrices." In Automata, Languages and Programming. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48523-6_68.

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Çatalyürek, Ümit V., and Cevdet Aykanat. "Decomposing irregularly sparse matrices for parallel matrix-vector multiplication." In Parallel Algorithms for Irregularly Structured Problems. Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/bfb0030098.

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Ghosh, Koustabh, Jonathan Fuchs, Parisa Amiri Eliasi, and Joan Daemen. "Universal Hashing Based on Field Multiplication and (Near-)MDS Matrices." In Progress in Cryptology - AFRICACRYPT 2023. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37679-5_6.

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Beierle, Christof, Thorsten Kranz, and Gregor Leander. "Lightweight Multiplication in $$GF(2^n)$$ with Applications to MDS Matrices." In Advances in Cryptology – CRYPTO 2016. Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-53018-4_23.

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Ren, Da Qi, and Reiji Suda. "Modeling and Optimizing the Power Performance of Large Matrices Multiplication on Multi-core and GPU Platform with CUDA." In Parallel Processing and Applied Mathematics. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14390-8_44.

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Stitt, Timothy, N. Stan Scott, M. Penny Scott, and Phil G. Burke. "2-D R-Matrix Propagation: A Large Scale Electron Scattering Simulation Dominated by the Multiplication of Dynamically Changing Matrices." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36569-9_23.

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Conference papers on the topic "Multiplication de matrices creuses"

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Ikeda, Kohei, Mitsumasa Nakajima, Shota Kita, Akihiko Shinya, Masaya Notomi, and Toshikazu Hashimoto. "High-Fidelity WDM-Compatible Photonic Processor for Matrix-Matrix Multiplication." In CLEO: Applications and Technology. Optica Publishing Group, 2024. http://dx.doi.org/10.1364/cleo_at.2024.jth2a.87.

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We experimentally demonstrate an 8 × 8 MZI-mesh photonic processor using silica-based waveguide technology. An accurate implementation of unitary matrices with high fidelity >0.96 over C-band was achieved, enabling matrix-matrix operation using wavelength multiplexing.

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Liang, Tianyu, Riley Murray, Aydın Buluç, and James Demmel. "Fast multiplication of random dense matrices with sparse matrices." In 2024 IEEE International Parallel and Distributed Processing Symposium (IPDPS). IEEE, 2024. http://dx.doi.org/10.1109/ipdps57955.2024.00014.

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Qian, Qiuming. "Optical full-parallel three matrices multiplication." In International Conference on Optoelectronic Science and Engineering '90. SPIE, 2017. http://dx.doi.org/10.1117/12.2294902.

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Tiskin, Alexander. "Fast distance multiplication of unit-Monge matrices." In Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial and Applied Mathematics, 2010. http://dx.doi.org/10.1137/1.9781611973075.103.

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Glushan, V. M., and Lozovoy A. Yu. "On Distributed Multiplication of Large-Scale Matrices." In 2021 IEEE 15th International Conference on Application of Information and Communication Technologies (AICT). IEEE, 2021. http://dx.doi.org/10.1109/aict52784.2021.9620434.

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Austin, Brian, Eric Roman, and Xiaoye Li. "Resilient Matrix Multiplication of Hierarchical Semi-Separable Matrices." In HPDC'15: The 24th International Symposium on High-Performance Parallel and Distributed Computing. ACM, 2015. http://dx.doi.org/10.1145/2751504.2751507.

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Ramamoorthy, Aditya, Li Tang, and Pascal O. Vontobel. "Universally Decodable Matrices for Distributed Matrix-Vector Multiplication." In 2019 IEEE International Symposium on Information Theory (ISIT). IEEE, 2019. http://dx.doi.org/10.1109/isit.2019.8849451.

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Buluc, Aydin, and John R. Gilbert. "On the representation and multiplication of hypersparse matrices." In Distributed Processing Symposium (IPDPS). IEEE, 2008. http://dx.doi.org/10.1109/ipdps.2008.4536313.

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Ballard, Grey, Aydin Buluc, James Demmel, et al. "Communication optimal parallel multiplication of sparse random matrices." In SPAA '13: 25th ACM Symposium on Parallelism in Algorithms and Architectures. ACM, 2013. http://dx.doi.org/10.1145/2486159.2486196.

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Labini, Paolo Sylos, Massimo Bernaschi, Werner Nutt, Francesco Silvestri, and Flavio Vella. "Blocking Sparse Matrices to Leverage Dense-Specific Multiplication." In 2022 IEEE/ACM Workshop on Irregular Applications: Architectures and Algorithms (IA3). IEEE, 2022. http://dx.doi.org/10.1109/ia356718.2022.00009.

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Reports on the topic "Multiplication de matrices creuses"

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Ballard, Grey, Aydin Buluc, James Demmel, et al. Communication Optimal Parallel Multiplication of Sparse Random Matrices. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada580140.

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