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Remove GPU code and add pointers to dedicated repository
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README.md

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@@ -4,6 +4,9 @@ GitHub repository for participants of the "Python for HPC" training.
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For information on the training, see the website
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[https://gjbex.github.io/Python-for-HPC/](https://gjbex.github.io/Python-for-HPC/)
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Note that material for a training on using GPUs in Python is in
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[another repository](https://github.com/gjbex/Python-on-GPUs).
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## What is it?
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source-code/README.md

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@@ -10,6 +10,7 @@ to create it. There is some material not covered in the presentation as well.
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* Packages (names listed taht can be used with `pip` or `conda` to install):
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* cython
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* dask
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* numba
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* numpy
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* numexpr
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* scipy
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* jupyter
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* ipywidgets
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* For the GPU code:
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* pycuda
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* scikit-cuda
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## What is it?
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1. `numpy-scipy`: some numpy/scipy codes for benchmakring.
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1. `pypy`: code to experiment with the Pypy interpreter.
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1. `file-formats`: influcence of file formats on performance.
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1. `gpu`: some examples of using GPUs.
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1. `performance`: general considerations about performance.
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**Note:** the GPU code in this repository was moved to
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[its own repository](https://github.com/gjbex/Python-on-GPUs)

source-code/gpu/README.md

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source-code/gpu/cudac_linux64_conda_specs.txt

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