Merge pull request #4 from gjbex/development

Development

Author: gjbex

docs/README.md

@@ -59,6 +59,13 @@ from scratch.  Some familiarity with numpy is required as well.
 If you plan to do Python GPU programming in a Linux or HPC environment (and you should), then familiarity with these environments is required as well.
 
 
+## Levels
+
+* Introductory: 20 %
+* Intermediate: 40 %
+* Advanced: 40 %
+
+
 ## Trainer(s)
 
   * Geert Jan Bex ([geertjan.bex@uhasselt.be](mailto:geertjan.bex@uhasselt.be))

source-code/README.md

@@ -5,6 +5,7 @@ Sample code for performing computations on a GPU.
 
 ## What is it?
 
-1. `pycuda`: directory illustrating pyCUDA.
+1. `pycuda`: code illustrating pyCUDA.
 1. `numba`: code illustrating using numba for GPU computing.
-1. `cupy`: Jupyter notebook illustrating some aspects of the `cupy` package.
+1. `cupy`: code illustrating some aspects of the `cupy` package.
+1. `cupynumeric`: code illustrating using cuPyNumeric for GPU computing.

source-code/cupynumeric/README.md

@@ -0,0 +1,10 @@
+# cuPyNumeric
+
+cuPyNumeric is a Python library that provides a GPU-accelerated drop-in
+replacement for NumPy. It is built on top of legion.
+
+
+## What is it?
+
+1. `environment.yml`: conda environment file for creating an environment
+   with the necessary dependencies.

source-code/cupynumeric/environment.yml

@@ -0,0 +1,10 @@
+name: python_on_gpus_cupynumeric
+channels:
+  - conda-forge
+dependencies:
+  - cupynumeric
+  - numpy
+  - scipy
+  - matplotlib
+  - jupyterlab
+prefix: /home/gjb/mambaforge/envs/python_on_gpus_cupynumeric