SuiteSparseQR is an implementation of the multifrontal sparse QR factorization method. Parallelism is exploited both in the BLAS and across different frontal matrices using Intel’s Threading Building Blocks, a shared-memory programming model for modern multicore architectures. It can obtain a substantial fraction of the theoretical peak performance of a multicore computer. The package is written in C++ with user interfaces for MATLAB, C, and C++. Both real and complex sparse matrices are supported.
Talk, session PS09 - Large-scale sparse matrix computationsInternational audienceno abstrac
International audienceThis article introduces a new systolic algorithm for QR factorization, and its...
International audienceThe advent of multicore processors requires to reconsider the design of high p...
SuiteSparseQR is a sparse multifrontal QR factorization algorithm. Dense matrix methods within each ...
International audienceThe advent of multicore processors represents a disruptive event in the histor...
To face the advent of multicore processors and the ever increasing complexity of hardware architectu...
Sparse linear systems occur in areas such as finite element methods and statistics. These system...
We present a parallel algorithm for the QR factorization with column pivoting of a sparse matrix by ...
International audienceTo face the advent of multicore processors and the ever increasing complexity ...
AbstractThis paper discusses an extension of the pipelined Givens method for computing the QR factor...
International audienceAs multicore systems continue to gain ground in the high‐performance computing...
Afin de s'adapter aux architectures multicoeurs et aux machines de plus en plus complexes, les modèl...
We describe the issues involved in the design and implementation of efficient parallel algorithms fo...
This paper discusses parGeMSLR, a C++/MPI software library for the solution of sparse systems of lin...
This article addresses the problems of memory man-agement in a parallel sparse matrix factorization ...
Talk, session PS09 - Large-scale sparse matrix computationsInternational audienceno abstrac
International audienceThis article introduces a new systolic algorithm for QR factorization, and its...
International audienceThe advent of multicore processors requires to reconsider the design of high p...
SuiteSparseQR is a sparse multifrontal QR factorization algorithm. Dense matrix methods within each ...
International audienceThe advent of multicore processors represents a disruptive event in the histor...
To face the advent of multicore processors and the ever increasing complexity of hardware architectu...
Sparse linear systems occur in areas such as finite element methods and statistics. These system...
We present a parallel algorithm for the QR factorization with column pivoting of a sparse matrix by ...
International audienceTo face the advent of multicore processors and the ever increasing complexity ...
AbstractThis paper discusses an extension of the pipelined Givens method for computing the QR factor...
International audienceAs multicore systems continue to gain ground in the high‐performance computing...
Afin de s'adapter aux architectures multicoeurs et aux machines de plus en plus complexes, les modèl...
We describe the issues involved in the design and implementation of efficient parallel algorithms fo...
This paper discusses parGeMSLR, a C++/MPI software library for the solution of sparse systems of lin...
This article addresses the problems of memory man-agement in a parallel sparse matrix factorization ...
Talk, session PS09 - Large-scale sparse matrix computationsInternational audienceno abstrac
International audienceThis article introduces a new systolic algorithm for QR factorization, and its...
International audienceThe advent of multicore processors requires to reconsider the design of high p...