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Move README to README.rst.

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commit a0667c3dec1e6ed8acdb01aa6f1bf4fdc2709509 1 parent b39910c
@inducer authored
Showing with 33 additions and 43 deletions.
  1. +0 −9 README
  2. +32 −0 README.rst
  3. +1 −34 setup.py
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9 README
@@ -1,9 +0,0 @@
-Hi there, welcome to PyCuda!
-----------------------------
-
-You can find installation instructions and documentation at
-
- http://mathema.tician.de/software/pycuda
-
-Have fun,
-Andreas
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32 README.rst
@@ -0,0 +1,32 @@
+PyCUDA lets you access `Nvidia <http://nvidia.com>`_'s `CUDA
+<http://nvidia.com/cuda/>`_ parallel computation API from Python.
+Several wrappers of the CUDA API already exist-so what's so special
+about PyCUDA?
+
+* Object cleanup tied to lifetime of objects. This idiom, often
+ called
+ `RAII <http://en.wikipedia.org/wiki/Resource_Acquisition_Is_Initialization>`_
+ in C++, makes it much easier to write correct, leak- and
+ crash-free code. PyCUDA knows about dependencies, too, so (for
+ example) it won't detach from a context before all memory
+ allocated in it is also freed.
+
+* Convenience. Abstractions like pycuda.driver.SourceModule and
+ pycuda.gpuarray.GPUArray make CUDA programming even more
+ convenient than with Nvidia's C-based runtime.
+
+* Completeness. PyCUDA puts the full power of CUDA's driver API at
+ your disposal, if you wish. It also includes code for
+ interoperability with OpenGL.
+
+* Automatic Error Checking. All CUDA errors are automatically
+ translated into Python exceptions.
+
+* Speed. PyCUDA's base layer is written in C++, so all the niceties
+ above are virtually free.
+
+* Helpful `Documentation <http://documen.tician.de/pycuda>`_ and a
+ `Wiki <http://wiki.tiker.net/PyCuda>`_.
+
+Relatedly, like-minded computing goodness for `OpenCL <http://khronos.org>`_
+is provided by PyCUDA's sister project `PyOpenCL <http://pypi.python.org/pypi/pyopencl>`_.
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35 setup.py
@@ -141,40 +141,7 @@ def main():
# metadata
version=ver_dic["VERSION_TEXT"],
description="Python wrapper for Nvidia CUDA",
- long_description="""
- PyCUDA lets you access `Nvidia <http://nvidia.com>`_'s `CUDA
- <http://nvidia.com/cuda/>`_ parallel computation API from Python.
- Several wrappers of the CUDA API already exist-so what's so special
- about PyCUDA?
-
- * Object cleanup tied to lifetime of objects. This idiom, often
- called
- `RAII <http://en.wikipedia.org/wiki/Resource_Acquisition_Is_Initialization>`_
- in C++, makes it much easier to write correct, leak- and
- crash-free code. PyCUDA knows about dependencies, too, so (for
- example) it won't detach from a context before all memory
- allocated in it is also freed.
-
- * Convenience. Abstractions like pycuda.driver.SourceModule and
- pycuda.gpuarray.GPUArray make CUDA programming even more
- convenient than with Nvidia's C-based runtime.
-
- * Completeness. PyCUDA puts the full power of CUDA's driver API at
- your disposal, if you wish. It also includes code for
- interoperability with OpenGL.
-
- * Automatic Error Checking. All CUDA errors are automatically
- translated into Python exceptions.
-
- * Speed. PyCUDA's base layer is written in C++, so all the niceties
- above are virtually free.
-
- * Helpful `Documentation <http://documen.tician.de/pycuda>`_ and a
- `Wiki <http://wiki.tiker.net/PyCuda>`_.
-
- Relatedly, like-minded computing goodness for `OpenCL <http://khronos.org>`_
- is provided by PyCUDA's sister project `PyOpenCL <http://pypi.python.org/pypi/pyopencl>`_.
- """,
+ long_description=open("README.rst", "rt").read(),
author="Andreas Kloeckner",
author_email="inform@tiker.net",
license = "MIT",
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