Loopy lets you easily generate the tedious, complicated code that is necessary to get good performance out of GPUs and multi-core CPUs. ---- Places on the web related to Loopy: * `Python package index `_ (download releases) Note the extra '.' in the PyPI identifier! .. image:: https://badge.fury.io/py/loo.py.png :target: http://pypi.python.org/pypi/loo.py * `Documentation `_ (read how things work) * `Github `_ (get latest source code, file bugs) * `Wiki `_ (read installation tips, get examples, read FAQ) * `Homepage `_ ---- 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 `_ and free for commercial, academic, and private use. All of Loopy's dependencies can be automatically installed from the package index after using:: pip install loo.py In addition, Loopy is compatible with and enhances `pyopencl `_.