This work has been directed toward the development of an efficient algorithm for performing this computation on the CYBER-203. The desire to provide software which gives the user the choice between the often conflicting goals of minimizing central processing (CPU) time or storage requirements has led to a diagonal-based algorithm in which one of three types of storage is selected for each diagonal. For each storage type, an initialization sub-routine estimates the CPU and storage requirements based upon results from previously performed numerical experimentation. These requirements are adjusted by weights provided by the user which reflect the relative importance the user places on the resources. The three storage types employed were chosen...
Abstract. On many high-speed computers the dense matrix technique is preferable to sparse matrix tec...
xi, 76 leaves : ill. ; 29 cm.The efficiency of linear algebra operations for sparse matrices on mode...
Sparse computations are ubiquitous in computational codes, with the sparse matrix-vector (SpMV) mult...
An important kernel of scientific software is the multiplication of a sparse matrix by a vector. The...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
This dissertation presents an architecture to accelerate sparse matrix linear algebra,which is among...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
This work is comprised of two different projects in numerical linear algebra. The first project is a...
To extract data from highly sophisticated sensor networks, algorithms derived from graph theory are ...
Matrix computations lie at the heart of most scientific computational tasks. The solution of linear ...
The thesis investigates the BLAS-3 routine of sparse matrix-matrix multiplication (SpGEMM) based on ...
In comparison to dense matrices multiplication, sparse matrices multiplication real performance for ...
A matrix having a high percentage of zero elements is called spares. In the solution of systems of l...
This report has been developed over the work done in the deliverable [Nava94] There it was shown tha...
Abstract. On many high-speed computers the dense matrix technique is preferable to sparse matrix tec...
xi, 76 leaves : ill. ; 29 cm.The efficiency of linear algebra operations for sparse matrices on mode...
Sparse computations are ubiquitous in computational codes, with the sparse matrix-vector (SpMV) mult...
An important kernel of scientific software is the multiplication of a sparse matrix by a vector. The...
AbstractThe matrix-vector multiplication operation is the kernel of most numerical algorithms.Typica...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
This dissertation presents an architecture to accelerate sparse matrix linear algebra,which is among...
Due to copyright restrictions, the access to the full text of this article is only available via sub...
This work is comprised of two different projects in numerical linear algebra. The first project is a...
To extract data from highly sophisticated sensor networks, algorithms derived from graph theory are ...
Matrix computations lie at the heart of most scientific computational tasks. The solution of linear ...
The thesis investigates the BLAS-3 routine of sparse matrix-matrix multiplication (SpGEMM) based on ...
In comparison to dense matrices multiplication, sparse matrices multiplication real performance for ...
A matrix having a high percentage of zero elements is called spares. In the solution of systems of l...
This report has been developed over the work done in the deliverable [Nava94] There it was shown tha...
Abstract. On many high-speed computers the dense matrix technique is preferable to sparse matrix tec...
xi, 76 leaves : ill. ; 29 cm.The efficiency of linear algebra operations for sparse matrices on mode...
Sparse computations are ubiquitous in computational codes, with the sparse matrix-vector (SpMV) mult...