Hauptseite > Publikationsdatenbank > Training course "Porting code from Matlab to Python" > print

001     857783
005     20210129235710.0
024 7 _ |a 2128/20192
|2 Handle
037 _ _ |a FZJ-2018-06750
100 1 _ |a Diaz, Sandra
|0 P:(DE-Juel1)165859
|b 0
|e Corresponding author
|u fzj
111 2 _ |c Jülich
|d 2018-10-08 - 2018-10-09
|w Germany
245 _ _ |a Training course "Porting code from Matlab to Python"
260 _ _ |c 2018
336 7 _ |a lecture
|2 DRIVER
336 7 _ |a Generic
|0 31
|2 EndNote
336 7 _ |a MISC
|2 BibTeX
336 7 _ |a Lecture
|b lecture
|m lecture
|0 PUB:(DE-HGF)17
|s 1586173003_15080
|2 PUB:(DE-HGF)
|x Other
336 7 _ |a LECTURE_SPEECH
|2 ORCID
336 7 _ |a Text
|2 DataCite
520 _ _ |a 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.
536 _ _ |a 511 - Computational Science and Mathematical Methods (POF3-511)
|0 G:(DE-HGF)POF3-511
|c POF3-511
|f POF III
|x 0
536 _ _ |a 574 - Theory, modelling and simulation (POF3-574)
|0 G:(DE-HGF)POF3-574
|c POF3-574
|f POF III
|x 1
536 _ _ |a SMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017)
|0 G:(DE-Juel1)HGF-SMHB-2013-2017
|c HGF-SMHB-2013-2017
|f SMHB
|x 2
536 _ _ |a HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)
|0 G:(EU-Grant)785907
|c 785907
|f H2020-SGA-FETFLAG-HBP-2017
|x 3
536 _ _ |a Virtual Connectomics - Deutschland - USA Zusammenarbeit in Computational Science: Mechanistische Zusammenhänge zwischen Struktur und funktioneller Dynamik im menschlichen Gehirn (BMBF-01GQ1504B)
|0 G:(DE-Juel1)BMBF-01GQ1504B
|c BMBF-01GQ1504B
|x 4
536 _ _ |a SLNS - SimLab Neuroscience (Helmholtz-SLNS)
|0 G:(DE-Juel1)Helmholtz-SLNS
|c Helmholtz-SLNS
|x 5
700 1 _ |a Deepu, Rajalekshmi
|0 P:(DE-Juel1)158021
|b 1
|u fzj
700 1 _ |a Peyser, Alexander
|0 P:(DE-Juel1)161525
|b 2
|u fzj
700 1 _ |a Klijn, Wouter
|0 P:(DE-Juel1)168169
|b 3
|u fzj
856 4 _ |u http://www.fz-juelich.de/SharedDocs/Termine/IAS/JSC/DE/Kurse/2018/matlab-2-python-2018.html?nn=2222554
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/Inroduction.pdf
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/Introduction_Classes_Iterators.pdf
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/S04_intro_numpy.pdf
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/S12_Intro_mpi.pdf
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/S6_Intro_tools.pdf
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/Workflow2018.pdf
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/Inroduction.pdf?subformat=pdfa
|x pdfa
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/Introduction_Classes_Iterators.pdf?subformat=pdfa
|x pdfa
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/S04_intro_numpy.pdf?subformat=pdfa
|x pdfa
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/S12_Intro_mpi.pdf?subformat=pdfa
|x pdfa
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/S6_Intro_tools.pdf?subformat=pdfa
|x pdfa
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/857783/files/Workflow2018.pdf?subformat=pdfa
|x pdfa
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:857783
|p openaire
|p open_access
|p VDB
|p driver
|p ec_fundedresources
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)165859
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)158021
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)161525
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)168169
913 1 _ |a DE-HGF
|b Key Technologies
|1 G:(DE-HGF)POF3-510
|0 G:(DE-HGF)POF3-511
|2 G:(DE-HGF)POF3-500
|v Computational Science and Mathematical Methods
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|l Supercomputing & Big Data
913 1 _ |a DE-HGF
|b Key Technologies
|l Decoding the Human Brain
|1 G:(DE-HGF)POF3-570
|0 G:(DE-HGF)POF3-574
|2 G:(DE-HGF)POF3-500
|v Theory, modelling and simulation
|x 1
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
914 1 _ |y 2018
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
980 _ _ |a lecture
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a UNRESTRICTED
980 1 _ |a FullTexts

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21