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.
* 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://tiker.net/doc/pycuda>`_.
<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.
* 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://tiker.net/doc/pycuda>`_.
Metadata
Release files for pycuda 0.90.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pycuda-0.90.1.tar.gz | 39.1 kB | Details |
Release files / pycuda-0.90.1.tar.gz
| Download URL | pycuda-0.90.1.tar.gz |
|---|---|
| Size | 39.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
1e1b3a104848e2b853954a7947d5a3fa78e5fc0ba1294f859ba862b7024aa0bb
|
|
BLAKE2b-256 checksum How to use checksums |
179a8e498d07a3781fcd8536269329b1e31572dc4ffac7e244c277b906398c1c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |