Posts by Collection

publications

Balanced Graph Partition Refinement using the Graph p-Laplacian

Published in PASC' 18: Proceedings of the Platform for Advanced Scientific Computing Conference., 2018

Simpson T, Pasadakis D, Kourounis D, Fujita K, Yamaguchi T, Ichimura T, Schenk O (2018) Balanced graph partition refinement using the graph p-laplacian. In: Proceedings of the Platform for Advanced Scientific Computing Conference, Association for Computing Machinery, New York, NY, USA, PASC ’18 https://doi.org/10.1145/3218176.3218232

talks

teaching

Linear Algebra

Bachelor's course, Università della Svizzera italiana (USI), 2020

Course syllabus

Linear mappings,linear spaces, Gauss method, vector spaces, linear maps and matrices, determinants, eigenvectors and eigenvalues. Course Link

High Performance Computing

MSc course, Università della Svizzera italiana (USI), 2021

Course syllabus

Numerical methods and HPC, large-scale scientific simulations, parallel programming models, HPC systems,scientific mathematical libraries, C programming language, linear algebra, mathematical optimization, partial differential equations. Course Link

Numerical Computing

Bachelor's course, Università della Svizzera italiana (USI), 2022

Course syllabus

Graph clustering, graph partitioning, solving linear systems of equations, page rank algorithm and large-scale nonlinear optimization, real-world applications. Course Link

High-Performance Computing Lab for CSE

Bachelor's course, ETH Zürich, 2022

Course syllabus

Computational Science and Engineering, HPC systems, parallel programming models, large-scale scientific simulations, performance analysis, parallelism detection, OpenMP, MPI, scientific mathematical libraries. Course Link