Fine granularity sparse QR factorization for multicore based systems

Authors:
Alfredo Buttari
Affiliations:
CNRS-IRIT, Toulouse, France
Venue:
PARA'10 Proceedings of the 10th international conference on Applied Parallel and Scientific Computing - Volume 2
Year:
2010

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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.