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docs/README.md

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## Schedule
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Total duration: 4 hours.
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| Subject | Duration |
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|---------------------------------------------|----------|
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| introduction and motivation | 5 min. |
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| performance and profiling | 25 min. |
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| libraries | 10 min. |
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| Cython | 60 min. |
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| coffee break | 10 min. |
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| interfacing with C/C++/Fortran | 30 min. |
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| multi-threaded programming | 10 min. |
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| MPI | 45 min. |
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| dask | 15 min. |
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| pyspark | 20 min. |
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| wrap up | 10 min. |
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Total duration: 8 hours.
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| Subject | Duration |
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|---------------------------------------------|-----------|
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| introduction and motivation | 5 min. |
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| performance and profiling | 25 min. |
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| libraries | 10 min. |
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| Cython | 90 min. |
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| interfacing with C/C++/Fortran | 60 min. |
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| multi-threaded programming | 60 min. |
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| MPI | 120 min. |
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| dask | 30 min. |
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| pyspark | 20 min. |
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| wrap up | 10 min. |
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## Training materials
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be familiar with these as well.
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## Level
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* Introductory: 10 %
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* Intermeidate: 30 %
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* Advanced: 60 %
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## Trainer(s)
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* Geert Jan Bex ([geertjan.bex@uhasselt.be](mailto:geertjan.bex@uhasselt.be))

python_for_hpc.pptx

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source-code/profiling/README.md

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1. `run_memory_prof.sh`: Bash shell script to create a memory profile.
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Note that this generates a lot of overhead in terms of CPU time.
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1. `cellular_automata.py`: example code to illustrate snakeviz.
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1. `microbenchmarking.ipynb`: some pitfalls when microbenchmarking
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Python code.

source-code/profiling/microbenchmarking.ipynb

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