Add to ORKGSparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the package is illustrated by a family of linear model tting functions that implement least squares methods for problems with sparse design matrices. Signicant performance improvements in memory utilization and computational speed are possible for applications involving large sparse matrices.
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
We describe an object oriented sparse matrix library in C++ designed for portability and performance...
ProceedingsSponsored by the Office of Naval Research and others.Bibliography: p. 191-210
SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the pack...
The purpose of this project was to provide sparse matrix functionality to the users of MATLAB*P. It ...
spam is an R package for sparse matrix algebra with emphasis on a Cholesky factor-ization of sparse ...
Sparse matrix computations arise in many scientific computing problems and for some (e.g.: iterative...
International audienceThe efficiency of a sparse linear algebra operation heavily relies on the abil...
Abstract. We have extended the matrix computation language and environment Matlab to include sparse ...
Today most real life applications require processing large amounts of data (i.e. ”Big Data”). The pa...
Vector computers have been extensively used for years in matrix algebra to treat with large dense ma...
In the last decade, the demand for statistical and computation methods for data analysis that involv...
The University of Florida Sparse Matrix Collection is a large, widely available, and actively growin...
This paper proposes a set of Level 3 Basic Linear Algebra Subprograms and associated kernels for sp...
We discuss the interface design for the Sparse Basic Linear Algebra Subprograms (BLAS), the kernels ...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
We describe an object oriented sparse matrix library in C++ designed for portability and performance...
ProceedingsSponsored by the Office of Naval Research and others.Bibliography: p. 191-210
SparseM provides some basic R functionality for linear algebra with sparse matrices. Use of the pack...
The purpose of this project was to provide sparse matrix functionality to the users of MATLAB*P. It ...
spam is an R package for sparse matrix algebra with emphasis on a Cholesky factor-ization of sparse ...
Sparse matrix computations arise in many scientific computing problems and for some (e.g.: iterative...
International audienceThe efficiency of a sparse linear algebra operation heavily relies on the abil...
Abstract. We have extended the matrix computation language and environment Matlab to include sparse ...
Today most real life applications require processing large amounts of data (i.e. ”Big Data”). The pa...
Vector computers have been extensively used for years in matrix algebra to treat with large dense ma...
In the last decade, the demand for statistical and computation methods for data analysis that involv...
The University of Florida Sparse Matrix Collection is a large, widely available, and actively growin...
This paper proposes a set of Level 3 Basic Linear Algebra Subprograms and associated kernels for sp...
We discuss the interface design for the Sparse Basic Linear Algebra Subprograms (BLAS), the kernels ...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to per...
We describe an object oriented sparse matrix library in C++ designed for portability and performance...
ProceedingsSponsored by the Office of Naval Research and others.Bibliography: p. 191-210