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Advanced Scientific Programming in Python
a Summer School by the G-Node and the
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture (FESB), University of Split
Tutors
Francesc Alted (francesc at blosc dot org)
Topics covered
- Memory efficient programming
- Compression
- multiprocessing with numexpr
- pandas (short overview)
- bcolz (compressed data management)
Lecture
The slides are here.
Exercises
Using your local machine
The exercises are here. Just download them (they are around 50 MB large, so be patient), unpack and launch ipython notebook:
$ tar xvfz starving-cpu-exercises.tar.gz $ cd starving-cpu-exercises $ ipython notebook
And do the exercises by following the guidelines in the “Split14-Starving-CPUs-Exercises.ipynb” notebook.
Using the Big Iron machine for heavy-duty exercises
Also, the GC3 group at University of Zurich generously provided a NUMA 48-core machine (SGI SV 100), and its usage is very much recommended for the multiprocessor and data storage exercises (exercises 5 and on). For using it, just download the next notebook and copy it to the Big Iron machine with:
$ scp split14-starving-cpus-exercises-bi.ipynb USER@login.gc3.uzh.ch:
(replace USER with your actual username).
Now, please launch an IPython kernel in the remote machine by following the next procedure, and you are ready to go.
Solution for the exercises
You can find them here.
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