|Когда:||Воскресенье, 13 сентября 2015, 11:15–12:50|
Are you interested in using Europe’s faster supercomputers (and getting ECTS credit points for doing so)? Would you like to learn how to write programs for parallel supercomputers, such as a Cray or a cluster of Graphics Processing Units? The course on supercomputing and simulations presents advanced topics in parallel computing and numerical simulation for prospective computational/software engineers. The course is designed to teach students how to program parallel computers to efficiently solve challenging problems in science and engineering, where very fast computers are required either to perform complex simulations or to analyze enormous datasets. It covers basic principles architectures, and algorithms of parallel systems. The course is structured in two parts: (i) introduction into supercomputing and applications, and (ii) and overview on basic graph partitioning parallel algorithm.
Olaf Schenk is a professor at the Institute of Computational Science within the Department of Informatics at the Universita della Svizzera italiana, Switzerland. He graduated in Applied Mathematics from Karlsruhe Institute of Technology (KIT), Germany, and earned his PhD in 2001 from the Department of Information Technology and Electrical Engineering of ETH Zurich, and a venia legendi from the Department of Mathematics and Computer Science from the University of Basel in 2009. He conducts research in numerical algorithms, computational science, and software tools for high-performance scientific computing. Olaf Schenk is a member of the Society for Industrial and Applied Mathematics (SIAM), the Association for Computing Machinery (ACM) and the Institute for Electrical and Electronic Engineers (IEEE). He is a recipient of an IBM faculty award (2009) and two leadership computing awards from the U.S. Department of Energy (2012, 2013). He serves on the editorial board of the SIAM Journal for Scientific Computing and on the project leadership team of the Swiss Platform for Advanced Scientific Computing (PASC).