An extended set of FORTRAN basic linear algebra subprograms
ACM Transactions on Mathematical Software (TOMS)
ACM Transactions on Mathematical Software (TOMS)
A set of level 3 basic linear algebra subprograms
ACM Transactions on Mathematical Software (TOMS)
Sparse extensions to the FORTRAN Basic Linear Algebra Subprograms
ACM Transactions on Mathematical Software (TOMS)
LAPACK's user's guide
A high performance algorithm using pre-processing for the sparse matrix-vector multiplication
Proceedings of the 1992 ACM/IEEE conference on Supercomputing
ACM Transactions on Mathematical Software (TOMS)
Basic Linear Algebra Subprograms for Fortran Usage
ACM Transactions on Mathematical Software (TOMS)
The automatic generation of sparse primitives
ACM Transactions on Mathematical Software (TOMS)
PSBLAS: a library for parallel linear algebra computation on sparse matrices
ACM Transactions on Mathematical Software (TOMS)
An updated set of basic linear algebra subprograms (BLAS)
ACM Transactions on Mathematical Software (TOMS)
ACM Transactions on Mathematical Software (TOMS)
Algorithm 818: A reference model implementation of the sparse BLAS in fortran 95
ACM Transactions on Mathematical Software (TOMS)
Hypergraph partitioning for automatic memory hierarchy management
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
On the development of PSBLAS-based parallel two-level Schwarz preconditioners
Applied Numerical Mathematics
ACM Transactions on Mathematical Software (TOMS)
An extensible global address space framework with decoupled task and data abstractions
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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Data and computation abstractions for dynamic and irregular computations
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Extending PSBLAS to build parallel schwarz preconditioners
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
Object-Oriented Techniques for Sparse Matrix Computations in Fortran 2003
ACM Transactions on Mathematical Software (TOMS)
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This article proposes a set of Level 3 Basic Linear Algebra Subprograms and associated kernels for sparse matrices. A major goal is to design and develop a common framework to enable efficient, and portable, implementations of iterative algorithms for sparse matrices on high-performance computers. We have designed the routines to shield the developer of mathematical software from most of the complexities of the various data structures used for sparse matrices. We have kept the interface and suite of codes as simple as possible while at the same time including sufficient functionality to cover most of the requirements of iterative solvers and sufficient flexibility to cover most sparse matrix data structures. An important aspect of our framework is that it can be easily extended to incorporate new kernels if the need arises. We discuss the design, implementation, and use of subprograms for the multiplication of a fully matrix by a sparse one and for the solution of sparse triangular systems with one or more (full) right-hand sides. We include a routine for checking the input data, generating a new sparse data structure from the input, and scaling a sparse matrix. The new data structure for the transformation can be specified by the user or can be chosen automatically by vendors to be efficient on their machines. We also include a routine for permuting the columns of a sparse matrix and one for permuting the rows of a full matrix.