Method and device for singular value and feature value composition of matrix on processing system

A technology for singular value decomposition and processing system, which is applied in the field of eigenvalue decomposition of matrices, and can solve problems such as computing performance degradation

Inactive Publication Date: 2009-10-21
IBM CORP
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Problems solved by technology

[0047] In view of the above problems, the present invention provides a method and device for singular value decomposition of a matrix and a method and device for eigenvalue decompo

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  • Method and device for singular value and feature value composition of matrix on processing system
  • Method and device for singular value and feature value composition of matrix on processing system
  • Method and device for singular value and feature value composition of matrix on processing system

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Embodiment Construction

[0063] The general idea of ​​the present invention is that, in the matrix decomposition process including the Givens rotation of the matrix, such as singular value decomposition and eigenvalue decomposition, instead of using the generated Givens rotation parameter group to perform Givens rotation on the intermediate matrix in each iteration, The Givens rotation parameter group is accumulated in the memory, and when the number of the accumulated Givens rotation parameter group reaches a specified threshold, the givens rotation parameter group is used to intensively perform Givens rotation on the intermediate matrix.

[0064] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0065] Figure 7 It is a flowchart of a method for singular value decomposition of a matrix on a processing system according to an embodiment of the present invention. like Figure 7 As shown, first, in step 705, for a given ...

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Abstract

The invention provides a method and a device for the singular value and feature value composition of a matrix on a processing system. The method for singular value composition includes: the matrix is converted into a bidiagonal matrix, and a sandwich matrix which needs to be converted into a singular vector matrix is obtained at the same time; submatrixes of which the elements are not zero are found out and converted in an iterative way on the vice diagonals in the bidiagonal matrix so that the bidiagonal matrix can be converged into a diagonal matrix and the sandwich matrix can be converted into the singular vector matrix; in each iterative step: Givens rotation parameter groups generated in the QR iterative processes of the submatrixes and the positions of the left boundary and the right boundary of the corresponding submatrixes which need to use the Givens rotation parameter groups in the sandwich matrix are accumulated in a memory; and when the number of the accumulated Givens rotation parameter groups reaches the preset threshold value, the Givens rotation parameter groups are utilized to carry out the Givens rotation of the sandwich matrix, wherein the threshold value is an integer which is higher than or equal to 2.

Description

technical field [0001] The present invention relates to the field of data processing, in particular, to a method and device for singular value decomposition of a matrix on a processing system and a method and device for eigenvalue decomposition of a matrix. Background technique [0002] LAPACK (Linear Algebra PACKage, linear algebra package) is a very effective, powerful and widely used linear algebra function library jointly developed by Oak Ridge National Laboratory, University of California, Davis, and University of Illinois, which is used in different high-performance computing environments. Efficiently solve numerical linear algebra problems, which has effectively worked for HPC (High Performance Computing) and computational science organizations for over 20 years. For details about LAPACK, please refer to http: / / netlib.amss.ac.cn / lapack / index.html. [0003] As a professional linear algebra library, LAPACK provides various linear algebra subroutines, including routines...

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Application Information

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IPC IPC(8): G06F17/16
Inventor 潘家铭龚志刚
Owner IBM CORP
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