ScaLAPACKThe paper presents a performance analysis of theQR eigensolver from ScaLAPACK library on the IBMRoadrunner machine. A ScaLAPACK-based testing platformwas developed in order to evaluate the performance of a parallelsolver to compute the eigenvalues and eigenvectors for largescalesparse matrices. ...
The QR decomposition of a matrix is an essential kernel for a variety of problems in scientific computing. It can be used to find a solution of a linear system, solve linear least squares or eigenvalue problems, estimate the rank of the matrix, and many...
Such factorization can be useful preconditioner for positive definite eigenvalue problems Kx = λx where the n × n (stiffness) matrix K is given by m × n natural factor A (K = A T A) which is sparse ...