Chapter 43: High performance linear algebra
Abstract
Linear algebra is fundamental to much of computational science. Applications involving PDEs come down to solving large systems of linear equation; solid state physics involves large eigenvalue systems. But even outside of engineering applications linear algebra is important: the major computational part of deep learning networks involves matrix-matrix multiplications.
Fields of Study & Subjects
Matrix Theory and Algorithms
Parallel Computing and Optimization Techniques
Numerical Methods and Algorithms
Publication details
- Journal / source
- Society for Industrial and Applied Mathematics eBooks
- Pages
- 437–442
- Publication date
- 19 January 2026
- Language
- EN
- Document type
- Book chapter