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Professor in the Department of Computer ScienceMCS 2022+44 (0) 191 33 42519

Biography

Book

T. Weinzierl: A Framework for Parallel PDE Solvers on Multiscale Adaptive Cartesian Grids. Verlag Dr. Hut, München, 2009.

This book is available online though I very much appreciate if you buy it from the publisher.

Book

M. Bader, H.-J. Bungartz and T. Weinzierl (ed.): Advanced Computing, Volume 93 of Lecture Notes in Computational Science and Engineering. Springer-Verlag, Heidelberg, Berlin, 2013.

Research interests

  • Scientific Computing
  • High-performance Computing
  • Parallel Algorithms

Research groups

  • Innovative Computing

Esteem Indicators

Publications

Authored book

Chapter in book

Conference Paper

Journal Article

Masters Thesis

  • Weinzierl, Tobias (2005). Eine cache-optimale Implementierung eines Navier-Stokes Lösers unter besonderer Berücksichtigung physikalischer Erhaltungssätze. Fakultät für Informatik, Technische Universität München Fakultät für Informatik, Technische Universität München. Masters.
  • Angermair, Gerald, Maier, Sonja & Weinzierl, Tobias (2003). Ein Maple-Java-Compiler für eine objektorientierte Maple-Erweiterung. Fakultät für Informatik, Technische Universität München Fakultät für Informatik, Technische Universität München. Masters.

Newspaper/Magazine Article

Presentation

  • Bader, M. & Weinzierl, T. (2014), Adaptivity - and Regular Cartesian Patches for the Shallow Water Equations and Vectorisation of an Augmented Riemann Solver for the Shallow Water Equations, SIAM Annual Meeting. Chicago, IL, SIAM.

Report

  • Atanasov, Atanas, Bungartz, Hans-Joachim & Weinzierl, Tobias (2013). A Toolkit for the Code Development in Advanced Computing.
  • Unterweger, Kristof, Weinzierl, Tobias, Ketcheson, David & Ahmadia, Aron (2013). PeanoClaw - A Functionally-Decomposed Approach to Adaptive Mesh Refinement with Local Time Stepping for Hyperbolic Conservation Law Solvers.
  • Jarema, Denis, Neumann, Philipp & Weinzierl, Tobias (2012). A Multiscale Approach for Particle Transport Simulation in Low Reynolds Number Flows.

Supervision students