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Showing 1 to 2 of 2 for “"Block krylov subspace methods"”.
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A new block Krylov subspace framework with applications to functions of matrices acting on multiple vectors
We propose a new framework for understanding block Krylov subspace methods, which hinges on a matrix-valued inner product. We can recast the ``classical" block Krylov methods, such as O'Leary's block conjugate gradients, global methods, and loop-interchange methods, within this framework. …
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Novel Monte Carlo Methods for Large-Scale Linear Algebra Operations
… to handle large data sets.</p> <p>Monte Carlo methods, which are based on statistical sampling, exhibit many attractive properties in dealing with large volume of datasets, including fast approximated results, memory efficiency, reduced data accesses, natural parallelism, and inherent fault …