Paketti: python-pycuda-dbg (2018.1.1-3) [contrib]

[ Source: pycuda  ]

Python module to access Nvidia‘s CUDA API (debug extensions)

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.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.

This package contains debug extensions build for the Python debug interpreter.

Tagit: Role: Debugging symbols

Muut pakettiin python-pycuda-dbg liittyvät paketit

• dep: libboost-python1.67.0

  Boost.Python Library

• dep: libboost-thread1.67.0

  portable C++ multi-threading

• dep: libc6 (>= 2.14)

  GNU-C-kirjasto: jaetut kirjastot
  myös näennäispaketti, jonka toteuttaa libc6-udeb

• dep: libcuda1 (>= 340)

  NVIDIA CUDA Driver Library

• dep: libcurand9.2

  NVIDIA cuRAND Library

• dep: libgcc1 (>= 1:3.0)

  GCC:n apukirjasto

• dep: libstdc++6 (>= 5.2)

  GNU standardi C++ -kirjasto, versio 3

• dep: python-dbg

  debug build of the Python Interpreter2 (version 2.7)

  dep: python-dbg (<< 2.8)

  dep: python-dbg (>= 2.7~)

• dep: python-numpy (>= 1:1.16.0~rc1)

  Numerical Python adds a fast array facility to the Python language

• dep: python-numpy-abi9

  näennäispaketti, jonka toteuttaa python-numpy

• dep: python-pycuda (= 2018.1.1-3)

  Python module to access Nvidia‘s CUDA parallel computation API

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Arkkitehtuuri	Paketin koko	Koko asennettuna	Tiedostot
amd64	5,959.3 kt	22,599.0 kt	[tiedostoluettelo]