Merge pull request #2 from gjbex/development

Sanitize conda environments

Author: gjbex

.gitignore

@@ -132,3 +132,6 @@ dmypy.json
 *.swp
 *~
 *.bak
+
+# direnv configuration file
+.envrc

README.md

@@ -10,12 +10,16 @@ For information on the training, see the website
 
 1. [`source-code`](source-code): sample code written to develop the slides and
    illustrate concepts.
-1. [`environment.yml`](environment.yml): conda environment file intended to be
-   cross-platform.
 1. [`python_on_gpus_science_linux64_conda_specs.txt`](python_on_gpus_linux64_conda_specs.txt):
    conda environment specification file specific for 64-bit Linux to precisely
    reproduce the environment on which the code was developed.
 1. [License](LICENSE): license information for the material in this repository.
 1. [Contributing](CONTRIBUTING.md): information on how to contribute to this
    repository.
 1. docs: directory containing the website for this repository.
+
+
+## Environment setup
+
+Each of the subdirectories of the `source-code` directory contains an `environment.yml`
+file that can be used to create a conda environment with the necessary packages.

environment.yml

@@ -5,10 +5,8 @@ Sample code for performing computations on a GPU.
 
 ## What is it?
 
-1. `pycuda.ipynb`: jupyter notebook illustrating pyCUDA.
-1. `curand.ipynb`: jupyter notebook illustrating generating random
-   numbers on a GPU.
-1. `scikit_cuda.ipynb`: jupyter notebook illustrating linear algebra
-   on a GPU device.
-1. `numba.ipynb`: jupyter notebook illustrating using numba for
-   GPU computing.
+1. `pycuda`: directory illustrating pyCUDA.
+1. `scikit_cuda`: code illustrating linear algebra on a GPU device.  This is an
+   older library and has been at least partially superceded by CuPy.
+1. `numba`: code illustrating using numba for GPU computing.
+1. `cupy`: Jupyter notebook illustrating some aspects of the `cupy` package.

source-code/README.md

@@ -0,0 +1,11 @@
+# CuPy
+
+CuPy serves as a "drop-in" replacement for numpy and (some) scipy with GPU support.
+
+
+## What is it?
+
+1. `environment.yml`: conda environment file specifying all dependencies
+   required to run the code.
+1. `cupy.ipynb`: Jupyter notebook illustrating how to use CuPy to perform
+   computations on a GPU.