Training course "Porting code from Matlab to Python"
(Course no. 105/2017 in the training programme of Forschungszentrum Jülich)
This course is fully booked. Further interested participants will be put on a waiting list.
Target audience: | This course is intended for master and PhD students, postdocs and scientists who want to enhance the performance of their scripts and algorithms currently running on Matlab. |
Contents: | |
Language: | The course is given in Englsih. |
Prerequisites: | Knowledge of Matlab. Basic knowledge of Python is recommended. No prior knowledge of MPI or supercomputer usage is required. |
Duration: | 2 days |
Date: | 9-10 October 2017, 09:00-16:30 |
Venue: | Jülich Supercomputing Centre, Ausbildungsraum 2, building 16.3, room 211 |
Number of participants: | minimum 5 |
Instructors: | Sandra Diaz, Lekshmi Deepu, Dr. Alexander Peyser, Wouter Klijn, JSC |
Contact: | Sandra Diaz Phone: +49 2461 61-8913 E-mail: s.diaz@fz-juelich.de |
Registration: | This course is fully booked. Further interested participants will be put on a waiting list. If you do not belong to the staff of Forschungszentrum Jülich, we need these data for registration: Given name, name, birthday, nationality, complete home address |
Python is becoming a popular language for scientific applications and is increasingly used for high performance computing. In this course we want to introduce Matlab programmers to the usage of Python. Matlab and Python have a comparable language philosophy, but Python can offer better performance using its optimizations and parallelization interfaces. Python also increases the portability and flexibility (interaction with other open source and proprietary software packages) of solutions, and can be run on supercomputing resources without high licensing costs.
The training course will be divided into three stages: First, attendants will learn how to do a direct translation of language concepts from Matlab to Python. Then, optimization of scripts using more Pythonic data structures and functions will be shown. Finally, code will be taken to the supercomputers where basic parallel programming (MPI) will be used to exploit parallelism in the computation.
The course will focus on numerical and statistical analysis as well as on image processing applications.
This course involves theoretical and hands on sessions which will be guided by experts in Python, Matlab and High Performance Computing. Attendants are highly encouraged to bring their own Matlab scripts.