14:15
14:15
11:30
Differentiable operad, Kuranishi correspondence, and the foundation of topological field theory
15:45
New developments in LAPACKJ and ScaLAPACK
Abstract
In this talk we shall be looking at recent and forthcoming developments in the widely used LAPACK and ScaLAPACK numerical linear algebra libraries.
Improvements include the following: Faster algorithms, better numerical methods, memory hierarchy optimizations, parallelism, and automatic performance tuning to accommodate new architectures; more accurate algorithms, and the use of extra precision; expanded functionality, including updating and downdating and new eigenproblems; putting more of LAPACK into ScaLAPACK; and improved ease of use with friendlier interfaces in multiple languages. To accomplish these goals we are also relying on better software engineering techniques and contributions from collaborators at many institutions.
After an overview, this talk will highlight new more accurate algorithms; faster algorithms, including those for pivoted Cholesky and updating of factorizations; and hybrid data formats.
This is joint work with Jim Demmel, Jack Dongarra and the LAPACK/ScaLAPACK team.
17:00
Convex and polyconvex functionals depending on higher order derivatives: partial regularity results
14:15
Electricity spot price modelling with non-Gaussian Ornstein-Uhlenbeck processes.
16:30
Analysis for the Nonlinear Electrolyte Wedge Problem
Abstract
This talk will discuss recent work on 3-phase junctions (electrolyte wedges)
in porous electrodes, including nonlinear reaction kinetics. Recent work on
reaction route representations (Kirchoff graphs) will also be discussed.
16:00
12:00
Team Meeting
Abstract
The modelling of the elastoplastic behaviour of single
crystals with infinite latent hardening leads to a nonconvex energy
density, whose minimization produces fine structures. The computation
of the quasiconvex envelope of the energy density involves the solution
of a global nonconvex optimization problem. Previous work based on a
brute-force global optimization algorithm faced huge numerical
difficulties due to the presence of clusters of local minima around the
global one. We present a different approach which exploits the structure
of the problem both to achieve a fundamental understanding on the
optimal microstructure and, in parallel, to design an efficient
numerical relaxation scheme.
This work has been carried out jointly with Carsten Carstensen
(Humboldt-Universitaet zu Berlin) and Sergio Conti (Universitaet
Duisburg-Essen)
17:00
15:45
17:00