Loopy lets you easily generate the tedious, complicated code that is necessary
to get good performance out of GPUs and multi-core CPUs.

Loopy's core idea is that a computation should be described simply and then
*transformed* into a version that gets high performance. This transformation
takes place under user control, from within Python.

It can capture the following types of optimizations:

* Vector and multi-core parallelism in the OpenCL/CUDA model
* Data layout transformations (structure of arrays to array of structures)
* Loopy Unrolling
* Loop tiling with efficient handling of boundary cases
* Prefetching/copy optimizations
* Instruction level parallelism
* and many more

Loopy targets array-type computations, such as the following:

* dense linear algebra,
* convolutions,
* n-body interactions,
* PDE solvers, such as finite element, finite difference, and
  Fast-Multipole-type computations

It is not (and does not want to be) a general-purpose programming language.

Loopy is licensed under the liberal `MIT license
<http://en.wikipedia.org/wiki/MIT_License>`_ and free for commercial, academic,
and private use. To use Loopy, you just need `pyopencl
<http://mathema.tician.de/software/pyopencl>`_.

Places on the web related to Loopy:

* `Python package index <http://pypi.python.org/pypi/loopy`_ (download releases) Note the extra '.' in the PyPI identifier!

* `Documentation <http://documen.tician.de/loopy>`_ (read how things work)
  .. image:: https://badge.fury.io/py/loo.py.png
      :target: http://pypi.python.org/pypi/loo.py
* `Github <http://github.com/pyopencl/loopy`_ (get latest source code, file bugs)
* `Wiki <http://wiki.tiker.net/Loopy`_ (read installation tips, get examples, read FAQ)