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Fine Granularity Sparse QR Factorization for Multicore Based Systems

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Applied Parallel and Scientific Computing (PARA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7134))

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Abstract

The advent of multicore processors represents a disruptive event in the history of computer science as conventional parallel programming paradigms are proving incapable of fully exploiting their potential for concurrent computations. The need for different or new programming models clearly arises from recent studies which identify fine-granularity and dynamic execution as the keys to achieve high efficiency on multicore systems. This work presents an implementation of the sparse, multifrontal QR factorization capable of achieving high efficiency on multicore systems through using a fine-grained, dataflow parallel programming model.

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Authors and Affiliations

  1. CNRS-IRIT, 118 route de Narbonne, F-31062, Toulouse, France

    Alfredo Buttari

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  1. Alfredo Buttari
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Kristján Jónasson

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Buttari, A. (2012). Fine Granularity Sparse QR Factorization for Multicore Based Systems. In: Jónasson, K. (eds) Applied Parallel and Scientific Computing. PARA 2010. Lecture Notes in Computer Science, vol 7134. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28145-7_23

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  • DOI: https://doi.org/10.1007/978-3-642-28145-7_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28144-0

  • Online ISBN: 978-3-642-28145-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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