Staff Lukas Troska, M.Sc.

Address:

Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI
Friedrich-Hirzebruch-Allee 7
53115 Bonn

Phone: +49 228 73-69788

Office: FHA7 2.023

E-Mail: ed tod nnob-inu tod sni ta aksorta tod b@foo tod de

Parallel-skalierbares Maschinelles Lernen Parallel-skalierbares Maschinelles Lernen Practical Lab, module P2E1.
Practical Lab Advanced Scientific Computing Efficient & User-friendly Parallel Implementation of Finite Difference Methods Practical Lab, module P4E2.
Practical Lab Numerical Simulation Programming Methods in Scientific Computing Practical Lab, module P4E1.
Programmierpraktikum Numerische Algorithmen Einführung in die Programmiermethoden des Wissenschaftlichen Rechnens Practical Lab, module P2E1.
Scalable Machine Learning Scalable Machine Learning Practical Lab, module P4E1.

HCM IRU Materials SEED Project.

A dimension-oblivious domain decomposition method based on space-filling curves. M. Griebel, M. A. Schweitzer, and L. Troska. SIAM Journal on Scientific Computing, 45(2):A369–A396, 2023. Also available as INS Preprint No. 2105. BibTeX PDF DOI
A fault-tolerant domain decomposition method based on space-filling curves. M. Griebel, M. A. Schweitzer, and L. Troska. Available as INS Preprint No. 2101, 2021. BibTeX PDF
Hpx smart executors. Z. Khatami, L. Troska, H. Kaiser, J. Ramanujam, and A. Serio. In Proceedings of the Third International Workshop on Extreme Scale Programming Models and Middleware, ESPM2'17, 3:1–3:8. New York, NY, USA, 2017. ACM. BibTeX DOI