An overview of the sparse basic linear algebra subprograms: The new standard from the BLAS technical forum

@article{Duff2002AnOO,
  title={An overview of the sparse basic linear algebra subprograms: The new standard from the BLAS technical forum},
  author={Iain S. Duff and M. Heroux and Roldan Pozo},
  journal={ACM Trans. Math. Softw.},
  year={2002},
  volume={28},
  pages={239-267}
}
We discuss the interface design for the Sparse Basic Linear Algebra Subprograms (BLAS), the kernels in the recent standard from the BLAS Technical Forum that are concerned with unstructured sparse matrices. [...] Key Method This design makes it easy to add further functionality to the sparse BLAS in the future.We illustrate the use of the Sparse BLAS with examples in the three supported programming languages, Fortran 95, Fortran 77, and C.Expand
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References

SHOWING 1-10 OF 28 REFERENCES
Algorithm 818: A reference model implementation of the sparse BLAS in fortran 95
TLDR
This paper describes here the Fortran 95 implementation intended as a reference model for the Sparse BLAS, and identifies the underlying complex issues of the representation and the handling of sparse matrices and gives suggestions to other implementors of how to address them. Expand
Level 3 basic linear algebra subprograms for sparse matrices: a user-level interface
TLDR
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 are discussed. Expand
The design of a new frontal code for solving sparse, unsymmetric systems
TLDR
The design, implementation, and performance of a frontal code for the solution of large, sparse, unsymmetric systems of linear equations, and the extensive use of higher-level BLAS kernels within MA42 are described. Expand
A Revised Proposal for a Sparse BLAS Toolkit
TLDR
An interface for routines which perform (i) sparse matrix times dense matrix product, (ii) the solution of a sparse triangular system with multiple right-hand-sides, (iii) the right permutation of aparse matrix and (iv) a check for the integrity of a dense matrix representation are described. Expand
Sparse extensions to the FORTRAN Basic Linear Algebra Subprograms
This paper describes an extension to the set of Basic Linear Algebra Subprograms. The extension is targeted at sparse vector operations, with the goal of providing efficient, but portable,Expand
An object-oriented framework for block preconditioning
TLDR
This article presents a framework to support preconditioning with various, possibly user-defined, data structures for matrices that are partitioned into blocks, and an upper layer of software which uses these blocks transparently of their data structure. Expand
AD-A 270 601 Segmented Operations for Sparse Matrix Computation on Vector Multiprocessors
TLDR
A new technique for sparse matrix multiplication on vector multiprocessors based on the efficient implementation of a segmented sum operation that is better suited than the Ellpack/Itpack or the Jagged Diagonal algorithms for matrices which have a varying number of non-zero elements in each row. Expand
Direct Methods for Sparse Matrices
The subject of sparse matrices has its roots in such diverse fields as management science, power systems analysis, surveying, circuit theory, and structural analysis. Mathematical models in all theseExpand
Templates for the solution of linear systems: building blocks for iterative methods
  • R. Barrett
  • Computer Science, Mathematics
  • Software, environments, tools
  • 1994
In this book, which focuses on the use of iterative methods for solving large sparse systems of linear equations, templates are introduced to meet the needs of both the traditional user and theExpand
Performance Modeling and Tuning of an Unstructured Mesh CFD Application
This paper describes performance tuning experiences with a three-dimensional unstructured grid Euler flow code from NASA, which we have reimplemented in the PETSc framework and ported to severalExpand
...
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