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Combining partial Jacobian computation and preconditioning: New heuristics, educational modules, and applications
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Solving problems originating from real-world applications is often based on the solution of a system of linear equations whose coefficient matrix is a large sparse Jacobian matrix. Hence, there is research to exploit the sparsity structure and to decrease the amount of storage. In contrast to full Jacobian computation in which all nonzero elements are to be determined, partial Jacobian computation is looking at a subset of these elements. Partial Jacobian computation can therefore be faster and more efficient than full Jacobian computation. Since Jacobian matrix-vector products are needed in iterative solvers, these types of linear systems can be efficiently solved using automatic differentiation. Determining these nonzero elements in full or partial Jacobian computations by automatic differentiation techniques can be modeled as graph coloring in the language of graph theory. On the other hand, preconditioning techniques are used to improve the convergence of iterative solvers and typically need access to all nonzero elements of the Jacobian matrix. So, a sparsification is applied to the Jacobian matrix before computing the preconditioner. In the second part of this thesis, we introduce a collection of interactive educational modules to teach not only graph coloring, but also other concepts from combinatorial scientific computing in the classroom. These modules are designed to involve the students more thoroughly in the process of learning. 104 pp. Deutsch. Nº de ref. del artículo: 9783736996366
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Combining partial Jacobian computation and preconditioning: New heuristics, educational modules, and applications
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Jentzsch-Cuvillier, Annette, 2017
ISBN 10: 3736996365
ISBN 13: 9783736996366
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnSolving problems originating from real-world applications is often based on the solution of a system of linear equations whose coefficient matrix is a large sparse Jacobian matrix. Hence, there is research to exploit the sparsity . Nº de ref. del artículo: 193776928
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Combining partial Jacobian computation and preconditioning: New heuristics, educational modules, and applications
Publicado por
Cuvillier, Cuvillier Okt 2017, 2017
ISBN 10: 3736996365
ISBN 13: 9783736996366
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Solving problems originating from real-world applications is often based on the solution of a system of linear equations whose coefficient matrix is a large sparse Jacobian matrix. Hence, there is research to exploit the sparsity structure and to decrease the amount of storage. In contrast to full Jacobian computation in which all nonzero elements are to be determined, partial Jacobian computation is looking at a subset of these elements. Partial Jacobian computation can therefore be faster and more efficient than full Jacobian computation. Since Jacobian matrix-vector products are needed in iterative solvers, these types of linear systems can be efficiently solved using automatic differentiation. Determining these nonzero elements in full or partial Jacobian computations by automatic differentiation techniques can be modeled as graph coloring in the language of graph theory. On the other hand, preconditioning techniques are used to improve the convergence of iterative solvers and typically need access to all nonzero elements of the Jacobian matrix. So, a sparsification is applied to the Jacobian matrix before computing the preconditioner. In the second part of this thesis, we introduce a collection of interactive educational modules to teach not only graph coloring, but also other concepts from combinatorial scientific computing in the classroom. These modules are designed to involve the students more thoroughly in the process of learning.Cuvillier Verlag, Nonnenstieg 8, 37075 Göttingen 104 pp. Deutsch. Nº de ref. del artículo: 9783736996366
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Combining partial Jacobian computation and preconditioning: New heuristics, educational modules, and applications
Impresión bajo demandaLibrería: AHA-BUCH GmbH, Einbeck, Alemania
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Solving problems originating from real-world applications is often based on the solution of a system of linear equations whose coefficient matrix is a large sparse Jacobian matrix. Hence, there is research to exploit the sparsity structure and to decrease the amount of storage. In contrast to full Jacobian computation in which all nonzero elements are to be determined, partial Jacobian computation is looking at a subset of these elements. Partial Jacobian computation can therefore be faster and more efficient than full Jacobian computation. Since Jacobian matrix-vector products are needed in iterative solvers, these types of linear systems can be efficiently solved using automatic differentiation. Determining these nonzero elements in full or partial Jacobian computations by automatic differentiation techniques can be modeled as graph coloring in the language of graph theory. On the other hand, preconditioning techniques are used to improve the convergence of iterative solvers and typically need access to all nonzero elements of the Jacobian matrix. So, a sparsification is applied to the Jacobian matrix before computing the preconditioner. In the second part of this thesis, we introduce a collection of interactive educational modules to teach not only graph coloring, but also other concepts from combinatorial scientific computing in the classroom. These modules are designed to involve the students more thoroughly in the process of learning. Nº de ref. del artículo: 9783736996366
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Combining partial Jacobian computation and preconditioning: New heuristics, educational modules, and applications
Impresión bajo demandaLibrería: preigu, Osnabrück, Alemania
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Taschenbuch. Condición: Neu. Combining partial Jacobian computation and preconditioning: New heuristics, educational modules, and applications | Mohammad Ali Rostami | Taschenbuch | 104 S. | Deutsch | 2017 | Cuvillier | EAN 9783736996366 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 110622778
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