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Object-Oriented Techniques for Sparse Matrix Computations in Fortran 2003
Abstract : The efficiency of a sparse linear algebra operation heavily relies on the ability of the sparse matrix storage format to exploit the computing power of the underlying hardware. Since no format is universally better than the others across all possible kinds of operations and computers, sparse linear algebra software packages should provide facilities to easily implement and integrate new storage formats within a sparse linear algebra application without the need to modify it; it should also allow to dynamically change a storage format at run-time depending on the specific operations to be performed. Aiming at these important features, we present an Object Oriented design model for a sparse linear algebra package which relies on Design Patterns. We show that an implementation of our model can be efficiently achieved through some of the unique features of the Fortran 2003 language. Experimental results show that the proposed software infrastructure improves the modularity and ease of use of the code at no performance loss.
Keywords :
Mathematics of computing
sparse matrices
Algorithms
Design Additional Key Words and Phrases: Sparse Matrices
Object-Oriented Design
D211 [Software Engineering]: Software Architectures-Data abstrac- tion
information hiding
structured
G13 [Numerical Analysis]: Numerical Linear Algebra-Sparse
G4 [Mathematical Software]: Algorithm design and analysis General Terms: Mathematics of computing
and very large systems (direct and iterative methods)
Cited literature [19 references]
https://hal.archives-ouvertes.fr/hal-02419121
Contributor : Alfredo Buttari Connect in order to contact the contributor
Submitted on : Tuesday, January 14, 2020 - 9:11:04 AM
Last modification on : Tuesday, October 19, 2021 - 2:24:21 PM
Long-term archiving on: : Wednesday, April 15, 2020 - 12:49:19 PM
Contributor : Alfredo Buttari Connect in order to contact the contributor
Submitted on : Tuesday, January 14, 2020 - 9:11:04 AM
Last modification on : Tuesday, October 19, 2021 - 2:24:21 PM
Long-term archiving on: : Wednesday, April 15, 2020 - 12:49:19 PM
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