Generating optimized sparse matrix vector product over finite fields

3Citations
Citations of this article
1Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Sparse Matrix Vector multiplication (SpMV) is one of the most important operation for exact sparse linear algebra. A lot of research has been done by the numerical community to provide efficient sparse matrix formats. However, when computing over finite fields, one need to deal with multi-precision values and more complex operations. In order to provide highly efficient SpMV kernel over finite field, we propose a code generation tool that uses heuristics to automatically choose the underlying matrix representation and the corresponding arithmetic. © 2014 Springer-Verlag.

Cite

CITATION STYLE

APA

Giorgi, P., & Vialla, B. (2014). Generating optimized sparse matrix vector product over finite fields. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8592 LNCS, pp. 685–690). Springer Verlag. https://doi.org/10.1007/978-3-662-44199-2_102

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free