Electrical & Computer Engin 697NA - ST-Numerical Algorithms
Spring
2017
01
3.00
Eric Polizzi
TU TH 2:30PM 3:45PM
UMass Amherst
16687
15253
Course description not available at this time.
Open to Graduate students only. Objectives: Provide a practical understanding of matrix computations for science, engineering and industrial applications;
Provide solid foundations in computational linear algebra; Introduction to parallel computing and programming practices
Contents: Introduction to Scientific Computing- Basic numerical techniques of linear algebra and their applications- Data formats and Practices - Matrix computations with an emphasis on solving sparse linear systems of equations and eigenvalue problems - Parallel architectures and parallel programming with OpenMP, MPI and hybrid -. Numerical parallel algorithms
Provide solid foundations in computational linear algebra; Introduction to parallel computing and programming practices
Contents: Introduction to Scientific Computing- Basic numerical techniques of linear algebra and their applications- Data formats and Practices - Matrix computations with an emphasis on solving sparse linear systems of equations and eigenvalue problems - Parallel architectures and parallel programming with OpenMP, MPI and hybrid -. Numerical parallel algorithms