A "nontransmit" packing routine was added to NASTRAN to allow matrix data to be refered to directly from the input/output buffer. Use of the packing routine permits various routines for matrix handling to perform a direct reference to the input/output buffer if data addresses have once been received. The packing routine offers a buffer by buffer backspace feature for efficient backspacing in sequential access. Unlike a conventional backspacing that needs twice back record for a single read of one record (one column), this feature omits overlapping of READ operation and back record. It eliminates the necessity of writing, in decomposition of a symmetric matrix, of a portion of the matrix to its upper triangular matrix from the last to the fi...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
Sparse matrix-vector multiplication (SpMxV) is one of the most important computational kernels in sc...
The 1992 NASTRAN release incorporates a number of improvements transparent to users. The NASTRAN exe...
In this dissertation we have identified vector processing shortcomings related to the efficient stor...
This program, REDUCE, reduces the bandwidth and profile of sparse symmetric matrices, using row and ...
A case history is presented in which the NASTRAN system provided both guidelines and working softwar...
Detailed computer resource measurements of the NASTRAN matrix decomposition spill logic were made us...
The authors describe a new extension to ScaLAPACK for computing with symmetric (Hermitian) matrices ...
Sparse matrix computations arise in many scientific computing problems and for some (e.g.: iterative...
There exist many storage formats for the in-memory representation of sparse matrices. Choosing the f...
SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the pack...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
Reviewed is the enhancement to NASTRAN program performed by NUK (Nippon Univac Kaisha, Ltd.) added t...
This report has been developed over the work done in the deliverable [Nava94] There it was shown tha...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
Sparse matrix-vector multiplication (SpMxV) is one of the most important computational kernels in sc...
The 1992 NASTRAN release incorporates a number of improvements transparent to users. The NASTRAN exe...
In this dissertation we have identified vector processing shortcomings related to the efficient stor...
This program, REDUCE, reduces the bandwidth and profile of sparse symmetric matrices, using row and ...
A case history is presented in which the NASTRAN system provided both guidelines and working softwar...
Detailed computer resource measurements of the NASTRAN matrix decomposition spill logic were made us...
The authors describe a new extension to ScaLAPACK for computing with symmetric (Hermitian) matrices ...
Sparse matrix computations arise in many scientific computing problems and for some (e.g.: iterative...
There exist many storage formats for the in-memory representation of sparse matrices. Choosing the f...
SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the pack...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
Reviewed is the enhancement to NASTRAN program performed by NUK (Nippon Univac Kaisha, Ltd.) added t...
This report has been developed over the work done in the deliverable [Nava94] There it was shown tha...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
The irregular nature of sparse matrix-vector multiplication, Ax = y, has led to the development of a...
Sparse matrix-vector multiplication (SpMxV) is one of the most important computational kernels in sc...