PDEs

Applied Mathematics School 2024

Sun, Dec 1 - Thu, Dec 5 2024

Internship Program

applied mathematics mathematics algorithms numerical methods PDEs stochastic algorithms machine learning computational science

The KAUST Applied Mathematics School is a 1-week visiting program aiming to introduce undergraduate and master's students to special research topics focusing on key areas in applied mathematics and computational science.

On Some PDEs with singular data

Prof. Mohammed Kbiri Alaoui, King Khalid University

Oct 25, 15:30 - 17:00

B1 L3 R3119

PDEs singular data

The aim of this talk is to investigate the following non local p-Laplacian problem with data a bounded Radon measure.

Device accelerated solvers for PDEs. Current status and future perspectives

Stefano Zampini, Senior Research Scientist, Hierarchical Computations on Manycore Architectures

Sep 26, 16:00 - 17:00

B5 L5 R5220

Shaheen GPU supercomputing petsc PDEs

In the next months, KAUST expects to place into service Shaheen-3, a supercomputer with a GPU partition whose planned 1 Exaflop/s HPL AI capability would rank it in the Top 6 globally if delivered today.

Jinchao Xu

Professor, Applied Mathematics and Computational Sciences

applied mathematics deep learning PDEs

Professor Xu is widely recognized as a leading figure in developing, designing and analyzing fast methods for finite element discretization and large-scale equation solutions.