python3-pycuda 2022.1~dfsg-1 (amd64 binary) in ubuntu kinetic
PyCUDA lets you access Nvidia‘s 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 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.
pycuda.
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.
.
This package contains Python 3 modules.
Details
- Package version:
- 2022.1~dfsg-1
- Status:
- Superseded
- Component:
- multiverse
- Priority:
- Optional
Downloadable files
- python3-pycuda_2022.1~dfsg-1_amd64.deb (307.5 KiB)
Package relationships
- Depends on:
- libboost-python1.74.0 (>= 1.74.0)
- libboost-thread1.74.0 (>= 1.74.0)
- libc6 (>= 2.32)
- libcurand10
- libgcc-s1 (>= 3.3.1)
- libnvidia-compute-510
- libstdc++6 (>= 11)
- nvidia-cuda-toolkit
- python3 (<< 3.11)
- python3 (>= 3.10~)
- python3
- python3-appdirs (>= 1.4.0)
- python3-decorator (>= 3.2.0)
- python3-mako
- python3-numpy (>= 1:1.20.0)
- python3-numpy-abi9
- python3-pytools
- Suggests:
- Recommends: