CSCI 8314: Sparse Matrix Computations

3 Credits

Sparsity and sparse matrices. Data structures for sparse matrices. Direct methods for sparse linear systems. Reordering techniques to reduce fill-in such as minimal degree ordering and nested dissection ordering. Iterative methods. Preconditioning algorithms. Algorithms for sparse eigenvalue problems and sparse least-squares. prereq: 5304 or numerical linear algebra course or instr consent

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All Instructors

A- Average (3.829)Most Common: A (59%)

This total also includes data from semesters with unknown instructors.

49 students
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  • 4.56



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