Study Programmes 2015-2016
INFO0939-1  
High performance scientific computing
Duration :
30h Th, 15h Pr, 20h Proj.
Number of credits :
Master in aerospace engineering (120 ECTS)5
Master in aerospace engineering (120 ECTS)5
Master in biomedical engineering (120 ECTS)5
Master in electrical engineering (120 ECTS)5
Master in electrical engineering (120 ECTS)5
Master in computer science and engineering (120 ECTS)5
Master in computer science and engineering (120 ECTS)5
Master in computer science (120 ECTS)5
Master in computer science (120 ECTS)5
Master in mechanical engineering (120 ECTS)5
Master in physical engineering (120 ECTS)5
Master in physical engineering (120 ECTS)4
Lecturer :
Christophe Geuzaine
Language(s) of instruction :
English language
Organisation and examination :
Teaching in the first semester, review in January
Units courses prerequisite and corequisite :
Prerequisite or corequisite units are presented within each program
Course contents :
Description of the course:
This course tackles advanced scientific calculation methods, both from a theoretical point of view and from the point of view of the implementation of high-performance applications.
Table of Contents:
The algorithms studied cover the following topics: interpolation, integration, solution of large linear systems, numerical methods for PDEs.
The course uses the C programming language for the efficient implementation of these algorithms, both serial and parallel. Practical work covers in detail the use of BLAS and LAPACK libraries and the parallelisation of algorithms using MPI and Open MP.
Learning outcomes of the course :
By the end of the course the students will have studied various advanced scientific computing algorithms. They will have learned the basics of their efficient implementation on serial and parallel computers, and will be familiar with the muticore (shared memory) programming paradigm using OpenMP, and the distributed memory programming paradigm using MPI.
Prerequisite knowledge and skills :
Mathematical analysis course; Numerical analysis course.
Planned learning activities and teaching methods :
Several homeworks.
Mode of delivery (face-to-face ; distance-learning) :
Face-to-face.
Recommended or required readings :
Cf. course website.
Assessment methods and criteria :
Written exam (1st and 2nd session) + homework.
Work placement(s) :
Organizational remarks :
This course is taught in English.
Contacts :
Prof. C. Geuzaine (Room: Montefiore Institute I155; Email(cgeuzaine@ulg.ac.be; )Homepage)