Patent ID: 9262799
Filing Date: 2016-02-16
CPC Classification: G06F,G06T

Claim Text:
1. A computerized method for computing eigenpairs of a large square matrix in a high performance computing (HPC) system having a plurality of nodes, each node including one or more processing cores for executing program threads, the nodes having non-uniform memory access, the method comprising: allocating the computing resources of the high performance computing system into a plurality of partitions, each partition comprising memory and a plurality of computer processor cores; allocating the computing resources of the one of the plurality of partitions into a plurality of partition nodes, each partition node comprising associated node memory and a plurality of the computer processor cores; segmenting the large square matrix of data into a plurality of digestible sub-matrices; storing the plurality of sub-matrices in a partition memory, which partition memory is accessible by each node, such that all of the sub-matrices are accessible by each of the nodes, the partition memory comprising the plurality of node memories; in a first phase, reducing the square matrix to band form by: in a second phase, reducing the band matrix to tridiagonal form by: in a third phase, computing eigenvectors and eigenvalues of the tridiagonal matrix by: determining the eigenpairs of the square matrix by in a fourth phase, transforming the eigenvectors of the tridiagonal matrix to eigenvectors of the band matrix by: in a fifth phase, transforming the eigenvectors of the band matrix to eigenvectors of the square matrix by: