Abstract
We present two parallel strategies to compute the inverse of a dense matrix, based on the so-called Sherman-Morrison algorithm and demonstrate their efficiency in memory and runtime on multicore CPU and GPU-equipped computers. Our methods are shown to be much more efficient than the direct method to compute the inverse of a nonsingular dense matrix, yielding up to 12 times faster performance on the CPU.
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He, X., Holm, M., Neytcheva, M. (2013). Parallel Implementation of the Sherman-Morrison Matrix Inverse Algorithm. In: Manninen, P., Öster, P. (eds) Applied Parallel and Scientific Computing. PARA 2012. Lecture Notes in Computer Science, vol 7782. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36803-5_15
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DOI: https://doi.org/10.1007/978-3-642-36803-5_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36802-8
Online ISBN: 978-3-642-36803-5
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