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| INFO0939-1 | High performance scientific computing
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| Duration : | 30h Th, 15h Pr, 20h Proj. |
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| Number of credits : |
| Master in Aerospace Engineering, research focus, 2nd year | | 5 |
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| Master in Aerospace Engineering, research focus, 2nd year | | 5 |
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| Master in Biomedical Engineering, research focus, 1st year | | 5 |
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| Master in Electrical Engineering, research focus, 2nd year | | 5 |
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| Master in Electrical Engineering, research focus, 2nd year | | 5 |
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| Master of science in computer science and engineering, research focus, 2nd year | | 5 |
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| Master in Computer science, Research Focus, 1st year | | 5 |
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| Master in Computer science, Research Focus, 1st year | | 5 |
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| Master in Engineering Physics, research focus, 1st year | | 5 |
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| Master in Engineering Physics, research focus, 2nd year | | 5 |
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| Master in Computer Science, Professional Focus (Management), 1st year | | 5 |
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| Master in Computer Science, Professional Focus (Management), 1st year | | 5 |
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| Master in Engineering Physics, specialized approach, 1st year | | 5 |
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| Master in Engineering Physics, specialized approach, 2nd year | | 5 |
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| Lecturer : | Christophe Geuzaine |
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Language(s) of instruction :
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| English language |
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Organisation and examination :
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| Teaching in the first semester, review in January |
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Course contents :
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| 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. |
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Learning outcomes of the course :
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| 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. |
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Prerequisites and co-requisites/ Recommended optional programme components :
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| Mathematical analysis course; Numerical analysis course. |
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Planned learning activities and teaching methods :
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| Several homeworks. |
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Mode of delivery (face-to-face ; distance-learning) :
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| Face-to-face. |
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Recommended or required readings :
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| Cf. course website. |
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Assessment methods and criteria :
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| Written exam (1st and 2nd session) + homework. |
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Work placement(s) :
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Organizational remarks :
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| This course is taught in English. |
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Contacts :
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| Prof. C. Geuzaine (Room: Montefiore Institute I155; Email(cgeuzaine@ulg.ac.be; )Homepage) |
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