Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 49 for “"Sparse matrices"”.
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Processing graphs and sparse matrices efficiently
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-05-01
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External Memory Algorithms for Factoring Sparse Matrices
<p>We consider the factorization of sparse symmetric matrices in the context of a two-layer storage system: disk/core. When the core is sufficiently large the factorization can be performed in-core. In this case we must read the input, compute, and write the output, in this sequence. On the other …
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A numerical engine for distributed sparse matrices
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
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Fill estimation for blocked sparse matrices and tensors
Many sparse matrices and tensors from a variety of applications, such as finite element methods and computational chemistry, have a natural aligned rectangular nonzero block structure. Researchers have designed high-performance blocked sparse operations which can take advantage of this sparse …
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An Object-Oriented Algorithmic Laboratory for Ordering Sparse Matrices
… known NP-hard problems that have applications in sparse matrix computations: the envelope/wavefront reduction problem and the fill reduction problem. Envelope/wavefront reducing orderings have a wide range of applications including profile and frontal solvers, incomplete factorization …
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Ordering Strategies for Sparse Matrices in Chemical Process Simulation
… of such machines to solve the large, sparse matrices which arise from such problems. Since the row and column ordering of these matrices has a direct impact on the efficiency of frontal methods, this work has developed a number of ordering strategies specifically designed for use with …
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A parallel fill estimation algorithm for sparse matrices and tensors in blocked formats
Many sparse matrices and tensors from a variety of applications, such as finite element methods and computational chemistry, have a natural aligned rectangular nonzero block structure. Researchers have designed high-performance blocked sparse operations which can take advantage of this sparsity …
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Multiprocessor sparse SVD algorithms and applications
… the singular value decomposition (SVD) of large sparse matrices on a multiprocessor architecture. We particularly consider the SVD of unstructured sparse matrices in which the number of rows may be substantially larger or smaller than the number of columns. On vector machines, considerable …
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Um modelo de malha irregular para o Método das Diferenças Finitas
… degree of efficiency, emphasizing the use of a sparse matrices technique in assembling the global system of equations.
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Diagonal Estimation with Probing Methods
Probing methods for trace estimation of large, sparse matrices has been studied for several decades. In recent years, there has been some work to extend these techniques to instead estimate the diagonal entries of these systems directly. We extend some analysis of trace estimators to their …
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Hypergraph-Based Combinatorial Optimization of Matrix -Vector Multiplication
… parallel matrix-vector multiplication for large sparse matrices. Parallel sparse matrix-vector multiplication is a particularly important numerical kernel in computational science. We have focused on optimizing the parallel performance of this operation by reducing the communication volume …
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An investigation of sparse tensor formats for tensor libraries
… Many naturally occurring tensors are considered sparse as they contain mostly zero values. As with sparse matrices, various techniques can be employed to more efficiently store and compute on these sparse tensors. This work explores several sparse tensor formats while ultimately evaluating two …
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A Low-Complexity Algorithm for Trajectory Generation in the Three-Body Problem
… the unique decomposition of a dense system into sparse matrices. Several relevant Cislunar trajectories are simulated using the algorithm, yielding favorable results in terms of arithmetic and time complexities over existing iterative techniques at the cost of accuracy. The algorithm does not …
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High-Performancs Sparse Matrix-Vector Multiplication on GPUS for Structured Grid Computations
In this thesis, we address efficient sparse matrix-vector multiplication for matrices arising from structured grid problems with high degrees of freedom at each grid node. Sparse matrix-vector multiplication is a critical step in the iterative solution of sparse linear systems of equations arising …
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Nearly tight oblivious subspace embeddings by trace inequalities
We present a new analysis of sparse oblivious subspace embeddings, based on the "matrix Chernoff" technique. These are probability distributions over (relatively) sparse matrices such that for any d-dimensional subspace of Rn, the norms of all vectors in the subspace are simultaneously …
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Implementation of symbolic model checking for probabilistic systems
… of conventional, explicit techniques, based on sparse matrices. We also propose a novel, hybrid approach, combining features of both symbolic and explicit implementations and show, using results from a wide range of case studies, that this technique can almost match the speed of sparse matrix …
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Data parallel algebraic multigrid
Algebraic multigrid methods for large, sparse linear systems are central to many computational simulations. Parallel algorithms for such solvers are generally decomposed into coarse-grain tasks suitable for distributed computers with traditional processing cores. Accelerating multigrid methods on …
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Sparse matrix-vector multiplication by specialization
… in the very common numerical procedure of sparse matrix-vector multiplication, in the case where a single matrix is to be multiplied by many vectors, is explored. The main objective is the evaluation of the speed-ups that can be obtained with program specialization without considering the …
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Algorithms incorporating concurrency and caching
… time. This thesis also introduces the compressed sparse rows (CSB) storage format for sparse matrices, which allows both Ax and ATx to be computed efficiently in parallel, where A is an n x n sparse matrix with nnz > n nonzeros and x is a dense n-vector. The parallel multiplication algorithm uses …
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Structural controllability of driftless bilinear control systems
… of driftless bilinear systems with sparse matrices. We begin with a rigorous introduction to the controllability of nonholonomic nonlinear systems. We present the notion of structural controllability and the fact that the controllability of linear systems is a generic property. We …
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