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Advanced scientific programming in matlab
02SFURV
A.A. 2021/22
Course Language
Inglese
Degree programme(s)
Doctorate Research in Ingegneria Elettrica, Elettronica E Delle Comunicazioni - Torino
Course structure
| Teaching | Hours |
|---|---|
| Lezioni | 20 |
| Esercitazioni in aula | 10 |
Lecturers
| Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut | Years teaching |
|---|---|---|---|---|---|---|---|
| Bardella Paolo | Professore Associato | IINF-01/A | 12,5 | 5 | 0 | 0 | 8 |
Co-lectures
Context
| SSD | CFU | Activities | Area context |
|---|---|---|---|
| *** N/A *** |
PERIOD: JANUARY - FEBRUARY
The course aims to provide advanced skills in scientific programming, and to teach sound methodologies for the development of reliable, optimized and maintainable codes.
A basic knowledge of MATLAB and the C language represents a prerequisite of this course.
During this course, many common methods used in Scientific Computing will be presented, with particular attention to the most recent programming techniques in MATLAB.
At the end of the course, the student will have expanded his/her knowledge of MATLAB and will be able to choose the best approach for the solution of numerical problem he/she will face.
Basic knowledge of MATLAB language.
1.5h: introduction to MATLAB, with particular attention on the latest improvements introduced in the language in the latest versions
1.0h: source Control systems integrated in MATLAB (git)
1.5h: MATLAB internals: data structures, JIT, numerical libraries (LAPACK, FFTW, …)
3.0h: object oriented programming in MATLAB
3.0h: optimization of MATLAB code, use of the Code Profiler
3.0h: MEX files for the execution of C/C++ and Fortran code in MATLAB. MATLAB C code generator
3.0h parallel computing in MATLAB: introduction to parallel computing, commands parfor, spmd, advantages and limitations.
3.0h: GPUs in MATLAB: introduction to GPUs and gpuarray command
3.0h: optimization of I/O in MATLAB, control of hardware
3.0h: fundamentals of machine learning in MATLAB; Big data and tall arrays
1.0h: alternatives to MATLAB: Arrayfire, Gnu Scientific library, Octave, Scilab
4.0h: projects' presentation
Mixed mode
Team project work development
P.D.1-1 - January