A new singular value decomposition algorithm suited to parallelization and preliminary results
ACST'06 Proceedings of the 2nd IASTED international conference on Advances in computer science and technology
Implementing a parallel matrix factorization library on the cell broadband engine
Scientific Programming - High Performance Computing with the Cell Broadband Engine
A new algorithm for singular value decomposition and its parallelization
Parallel Computing
High-performance bidiagonal reduction using tile algorithms on homogeneous multicore architectures
ACM Transactions on Mathematical Software (TOMS)
An improved parallel singular value algorithm and its implementation for multicore hardware
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
| Hi-index | 0.00 |
A parallel algorithm for computing the singular value decomposition of a matrix is presented. The algorithm uses a divide and conquer procedure based on a rank one modification of a bidiagonal matrix. Numerical difficulties associated with forming the product of a matrix with its transpose are avoided, and numerically stable formulae for obtaining the left singular vectors after computing updated right singular vectors are derived. A deflation technique is described that, together with a robust root finding method, assures computation of the singular values to full accuracy in the residual and also assures orthogonality of the singular vectors.