Joint SimTech/Math-Colloquium: Balancing Inexactness in Matrix Computations (Erin Carson)

July 13, 2023, 4:00 p.m. (CEST)

Time: July 13, 2023, 4:00 p.m. (CEST)
Download as iCal:

Date: 13 July 2023
Place: Pfaffenwaldring 57 (NWZ II), Room 8.122
Time: 4pm

We warmly invite you to the joint colloquium of SimTech and the Math Department for a talk by Erin Carson. She is Assistant Professor in the Department of Numerical Mathematics, Faculty of Mathematics and Physics, Charles University in Prague. Her research sits at the intersection of numerical linear algebra, high performance computing, and parallel algorithms. In 2022, Erin Carson received an ERC Starting Grant. She will analyse numerical computations and search for new algorithms for computational systems.

On supercomputers that exist today, achieving even close to the peak performance is incredibly difficult if not impossible for many applications. Techniques designed to improve the performance of matrix computations - making computations less expensive by reorganizing an algorithm, making intentional approximations, and using lower precision - all introduce what we can generally call ``inexactness''. The questions to ask are then:

1. With all these various sources of inexactness involved, does a given algorithm still get close enough to the right answer?
2. Given a user constraint on required accuracy, how can we best exploit and balance different types of inexactness to improve performance?

Studying the combination of different sources of inexactness can thus reveal not only limitations, but also new opportunities for developing algorithms for matrix computations that are both fast and provably accurate. We present recent results towards this goal, including mixed precision randomized decompositions and mixed precision sparse approximate inverse preconditioners.


To the top of the page