From c750933256a70ebda71c22c5d7c68ef537313ddd Mon Sep 17 00:00:00 2001
From: Bartosz Wozniak <bdw10@ic.ac.uk>
Date: Thu, 17 Apr 2014 03:02:38 +0200
Subject: [PATCH] Added info to README

Included simple description of the software, installation and usage
instructions.
---
 README.rst | 60 +++++++++++++++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 59 insertions(+), 1 deletion(-)

diff --git a/README.rst b/README.rst
index 3fd3c91..01213b1 100644
--- a/README.rst
+++ b/README.rst
@@ -1,4 +1,62 @@
 GiMMiK
 ======
+Generator of Matrix Multiplication Kernels - GiMMiK - is a tool for generation of high performance matrix multiplication kernel code for various accelerator platforms. Currently CUDA and OpenCL are the only supported platforms.
 
-Generator of Matrix Multiplication Kernels
+What does GiMMiK do?
+--------------------
+Consider matrix multiplication of the form
+
+C = α ∙ A ⨉ B + β ∙ C
+
+GiMMiK generates fully unrolled kernels, highly specialised to a given operator matrix. The generated code is fully unrolled - each kernel computes a single column of the output matrix. GiMMiK was designed to perform well in a Block by Panel type of matrix multiplication where the operator matrix is small. GiMMiK also removes any sparsity form the operator matrix as well as attempts to reduce common sub-expressions.
+
+How do I install GiMMiK?
+------------------------
+Clone the git repository and use `setup.py` to install the GiMMiK package. You will need the following dependencies:
+
+* `mako <http://www.makotemplates.org/>`_
+* `numpy >= 1.7 <http://www.numpy.org/>`_
+
+Once obtained, you can install GiMMiK by running
+
+::
+
+    python setup.py install
+
+to perform a system-wide install. Alternatively, run
+::
+
+    python setup.py install --user
+
+to install the package locally.
+
+If you desire to test whether GiMMiK works correctly on your system, you can do so by running:
+::
+
+    python setup.py test
+
+To execute the tests you will need these additional dependencies:
+
+* `CUDA <https://developer.nvidia.com/cuda-downloads>`_ + `pycuda >= 2011.2 <http://mathema.tician.de/software/pycuda/>`_
+* OpenCL + `pyopencl >= 2013.2 <http://mathema.tician.de/software/pyopencl/>`_
+
+How do I use GiMMiK?
+--------------------
+Once installed, you are ready to use GiMMiK.
+
+.. code:: python
+
+    import gimmik.generator as gen
+    from gimmik.platform import Platform
+
+    ...
+
+    # Generate kernel
+    kernel = gen.generateKernel(data, alpha=2.0, beta=3.0, double=True, reduced=True,
+                                platform=Platform.OPENCL)
+
+    ...
+
+Who uses GiMMiK?
+----------------
+GiMMiK was develop to improve performance of the `PyFR <http://www.pyfr.com>`_ framework for solving advection-diffusion type problems in the area of CFD.
\ No newline at end of file