The block Gram–Schmidt method computes the qr factorisation rapidly, but this is dependent on block size m. We endeavor to deter-mine the optimalm automatically during one execution. Our algorithm determines m through observing the relationship between computa-tion time and complexity. Numerical experiments show that our pro-posed algorithms compute approximately twice as fast as the block Gram–Schmidt method for some block sizes, and is a viable option for computing the qr factorisation in a more stable and rapid manner. Subject class: 65F10, 65M1
The QR-algorithm is a renowned method for computing all eigenvalues of an arbitrary matrix. A prelim...
We compare implementations of two integer factorization algorithms, the elliptic curve method (ECM) ...
The Cholesky QR algorithm is an efficient communication-minimizing algorithm for computing the QR fa...
The block Gram--Schmidt method computes the QR factorisation rapidly, but this is dependent on block...
AbstractA new form of the QR factorization procedure is presented which is based on a generalization...
Abstract Because of an imbalance between computation and memory speed in modern processors, programm...
This article describes a suite of codes as well as associated testing and timing drivers for computi...
The advent of supercomputers with hierarchical memory systems has imposed the use of block algorithm...
We propose a block version of the randomized Gram-Schmidt process for computing a QR factorization o...
A statically scheduled parallel block QR factorization procedure is described. It is based on "bloc...
The QR algorithm is the method of choice for computing all eigenvalues of a dense nonsymmetric matri...
International audienceWe present parallel and sequential dense QR factorization algorithms that are ...
The solution of dense systems of linear equations is at the heart of numerical computations. Such sy...
Two recent approaches 4, 14 in subspace identification problems require the computation of the R fac...
The mathematical area of integer factorization has gone a long way since the early days of Pierre de...
The QR-algorithm is a renowned method for computing all eigenvalues of an arbitrary matrix. A prelim...
We compare implementations of two integer factorization algorithms, the elliptic curve method (ECM) ...
The Cholesky QR algorithm is an efficient communication-minimizing algorithm for computing the QR fa...
The block Gram--Schmidt method computes the QR factorisation rapidly, but this is dependent on block...
AbstractA new form of the QR factorization procedure is presented which is based on a generalization...
Abstract Because of an imbalance between computation and memory speed in modern processors, programm...
This article describes a suite of codes as well as associated testing and timing drivers for computi...
The advent of supercomputers with hierarchical memory systems has imposed the use of block algorithm...
We propose a block version of the randomized Gram-Schmidt process for computing a QR factorization o...
A statically scheduled parallel block QR factorization procedure is described. It is based on "bloc...
The QR algorithm is the method of choice for computing all eigenvalues of a dense nonsymmetric matri...
International audienceWe present parallel and sequential dense QR factorization algorithms that are ...
The solution of dense systems of linear equations is at the heart of numerical computations. Such sy...
Two recent approaches 4, 14 in subspace identification problems require the computation of the R fac...
The mathematical area of integer factorization has gone a long way since the early days of Pierre de...
The QR-algorithm is a renowned method for computing all eigenvalues of an arbitrary matrix. A prelim...
We compare implementations of two integer factorization algorithms, the elliptic curve method (ECM) ...
The Cholesky QR algorithm is an efficient communication-minimizing algorithm for computing the QR fa...