معرفی شرکت ها

cuvec-2.9.0

Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

توضیحات

Unifying Python/C++/CUDA memory: Python buffered array -> C++11 `std::vector` -> CUDA managed memory
ویژگی مقدار
سیستم عامل -
نام فایل cuvec-2.9.0
نام cuvec
نسخه کتابخانه 2.9.0
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Casper da Costa-Luis
ایمیل نویسنده casper.dcl@physics.org
آدرس صفحه اصلی https://github.com/AMYPAD/CuVec
آدرس اینترنتی https://pypi.org/project/cuvec/
مجوز MPL-2.0
CuVec ===== Unifying Python/C++/CUDA memory: Python buffered array ↔ C++11 ``std::vector`` ↔ CUDA managed memory. |Version| |Downloads| |Py-Versions| |DOI| |Licence| |Tests| |Coverage| .. contents:: Table of contents :backlinks: top :local: Why ~~~ Data should be manipulated using the existing functionality and design paradigms of each programming language. Python code should be Pythonic. CUDA code should be... CUDActic? C code should be... er, Clean. However, in practice converting between data formats across languages can be a pain. Other libraries which expose functionality to convert/pass data formats between these different language spaces tend to be bloated, unnecessarily complex, and relatively unmaintainable. By comparison, ``cuvec`` uses the latest functionality of Python, C/C++11, and CUDA to keep its code (and yours) as succinct as possible. "Native" containers are exposed so your code follows the conventions of your language. Want something which works like a ``numpy.ndarray``? Not a problem. Want to convert it to a ``std::vector``? Or perhaps a raw ``float *`` to use in a CUDA kernel? Trivial. - Less boilerplate code (fewer bugs, easier debugging, and faster prototyping) - Fewer memory copies (faster execution) - Lower memory usage (do more with less hardware) Non objectives -------------- Anything to do with mathematical functionality. The aim is to expose functionality, not create it. Even something as simple as setting element values is left to the user and/or pre-existing features - for example: - Python: ``arr[:] = value`` - NumPy: ``arr.fill(value)`` - CuPy: ``cupy.asarray(arr).fill(value)`` - C++: ``std::fill(vec.begin(), vec.end(), value)`` - C & CUDA: ``memset(vec.data(), value, sizeof(T) * vec.size())`` Install ~~~~~~~ Requirements: - Python 3.7 or greater (e.g. via `Anaconda or Miniconda <https://docs.conda.io/projects/conda/en/latest/user-guide/install/download.html#anaconda-or-miniconda>`_ or via `python3-dev`) - (optional) `CUDA SDK/Toolkit <https://developer.nvidia.com/cuda-downloads>`_ (including drivers for an NVIDIA GPU) * note that if the CUDA SDK/Toolkit is installed *after* CuVec, then CuVec must be re-installed to enable CUDA support .. code:: sh pip install cuvec Usage ~~~~~ See `the usage documentation <https://amypad.github.io/CuVec/#usage>`_ and `quick examples <https://amypad.github.io/CuVec/#examples>`_ of how to upgrade a Python ↔ C++ ↔ CUDA interface. External Projects ~~~~~~~~~~~~~~~~~ For integration into Python, C++, CUDA, CMake, and general SWIG projects, see `the external project documentation <https://amypad.github.io/CuVec/#external-projects>`_. Full and explicit example modules using the `CPython API <https://github.com/AMYPAD/CuVec/tree/main/cuvec/src/example_mod>`_ and `SWIG <https://github.com/AMYPAD/CuVec/tree/main/cuvec/src/example_swig>`_ are also provided. Contributing ~~~~~~~~~~~~ See `CONTRIBUTING.md <https://github.com/AMYPAD/CuVec/blob/main/CONTRIBUTING.md>`_. Licence ~~~~~~~ |Licence| |DOI| Copyright: - `Casper O. da Costa-Luis <https://github.com/casperdcl>`__ @ University College London/King's College London - `Contributors <https://github.com/AMYPAD/cuvec/graphs/contributors>`__ .. |DOI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.4446211.svg :target: https://doi.org/10.5281/zenodo.4446211 .. |Licence| image:: https://img.shields.io/pypi/l/cuvec.svg?label=licence :target: https://github.com/AMYPAD/CuVec/blob/main/LICENCE .. |Tests| image:: https://img.shields.io/github/actions/workflow/status/AMYPAD/CuVec/test.yml?branch=main&logo=GitHub :target: https://github.com/AMYPAD/CuVec/actions .. |Downloads| image:: https://img.shields.io/pypi/dm/cuvec.svg?logo=pypi&logoColor=white&label=PyPI%20downloads :target: https://pypi.org/project/cuvec .. |Coverage| image:: https://codecov.io/gh/AMYPAD/CuVec/branch/main/graph/badge.svg :target: https://codecov.io/gh/AMYPAD/CuVec .. |Version| image:: https://img.shields.io/pypi/v/cuvec.svg?logo=python&logoColor=white :target: https://github.com/AMYPAD/CuVec/releases .. |Py-Versions| image:: https://img.shields.io/pypi/pyversions/cuvec.svg?logo=python&logoColor=white :target: https://pypi.org/project/cuvec


زبان مورد نیاز

مقدار نام
>=3.7 Python


نحوه نصب


نصب پکیج whl cuvec-2.9.0:

    pip install cuvec-2.9.0.whl


نصب پکیج tar.gz cuvec-2.9.0:

    pip install cuvec-2.9.0.tar.gz