منابع مشابه
An Approach to Automatic Tuning for Parallel Householder QR Decomposition
We consider parallel computing of the Householder QR decomposition on SMP machines. This decomposition is one of the basic tools in matrix computations and is used in various problems such as the least square problem and the singular value decomposition of a rectangular matrix. Since this algorithm consists almost entirely of BLAS routines such as matrix-vector multiplications, the simplest way...
متن کاملSparse Householder QR Factorization on a Mesh
In this document we are going to analyze the pa-rallelization of QR factorization by means of House-holder transformations. This parallelization will be carried out on a machine with a mesh topology (a 2-D torus to be more precise). We use a cyclic distribution of the elements of the sparse matrix M we want to decompose over the processors. Each processor represents the nonzero elements of its ...
متن کاملSparse Householder QR Factorization on a MeshRam
In this document we are going to analyze the pa-rallelization of QR factorization by means of House-holder transformations. This parallelization will be carried out on a machine with a mesh topology (a 2-D torus to be more precise). We use a cyclic distribution of the elements of the sparse matrix M we want to decompose over the processors. Each processor represents the nonzero elements of its ...
متن کاملVector and Parallel Tuning of Solid Earth Simulation Codes - GeoFEM and Householder QR Decomposition -
In this paper, we discuss vector and parallel tuning of GeoFEM and the Householder QR decomposition process being solid earth simulation codes. Process of GeoFEM code can be roughly divided into two parts, Matrix Assemble part and Solver part. Currently, GeoFEM's parallel iterative solver has attained good parallel and vector performance, and GeoFEM's Matrix Assemble part has attained good para...
متن کاملHouseholder QR Factorization With Randomization for Column Pivoting (HQRRP)
A fundamental problem when adding column pivoting to the Householder QR factorization is that only about half of the computation can be cast in terms of high performing matrixmatrix multiplications, which greatly limits the benefits that can be derived from so-called blocking of algorithms. This paper describes a technique for selecting groups of pivot vectors by means of randomized projections...
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ژورنال
عنوان ژورنال: Transactions of the Society of Instrument and Control Engineers
سال: 1993
ISSN: 0453-4654
DOI: 10.9746/sicetr1965.29.1199