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In this program

Implementation on modern architectures (vectorization, parallelism overview)
Large-scale sparse linear solvers in practice
Uncertainty quantification
Monte Carlo methods
Inverse problems
Regularization (Tikhonov)
Validation against analytical
Experimental benchmarks

High-performance and applied computation

Large-scale sparse linear solvers in practice

Numerical analysis · STEM / applied

Topic

Large-scale sparse linear solvers in practice

Practice by unit: High-performance and applied computation

Graduate Numerical Analysis — scope drawn from open graduate numerical analysis texts and typical US graduate numerical analysis syllabi.

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