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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


Francesc Alted (francesc at blosc dot org)

Topics covered
  • Memory efficient programming
  • Compression
  • multiprocessing with numexpr
  • pandas (short overview)
  • bcolz (compressed data management)

The slides are here.


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

(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.

starving_cpu.txt · Last modified: 2014/09/12 16:14 by francesc

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