NCCL (pronounced "Nickel") is a stand-alone library of standard collective communication routines for GPUs, implementing all-reduce, all-gather, reduce, broadcast, and reduce-scatter. It has been optimized to achieve high bandwidth on any platform using PCIe, NVLink, NVswitch, as well as networking using InfiniBand Verbs or TCP/IP sockets.
Raw data
{
"_id": null,
"home_page": "https://developer.nvidia.com/cuda-zone",
"name": "nvidia-nccl-cu12",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3",
"maintainer_email": null,
"keywords": "cuda, nvidia, runtime, machine learning, deep learning",
"author": "Nvidia CUDA Installer Team",
"author_email": "compute_installer@nvidia.com",
"download_url": null,
"platform": null,
"description": "NCCL (pronounced \"Nickel\") is a stand-alone library of standard collective communication routines for GPUs, implementing all-reduce, all-gather, reduce, broadcast, and reduce-scatter. It has been optimized to achieve high bandwidth on any platform using PCIe, NVLink, NVswitch, as well as networking using InfiniBand Verbs or TCP/IP sockets.\n",
"bugtrack_url": null,
"license": "BSD-3-Clause",
"summary": "NVIDIA Collective Communication Library (NCCL) Runtime",
"version": "2.23.4",
"project_urls": {
"Homepage": "https://developer.nvidia.com/cuda-zone"
},
"split_keywords": [
"cuda",
" nvidia",
" runtime",
" machine learning",
" deep learning"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "c83a0112397396dec37ffc8edd7836d48261b4d14ca60ec8ed7bc857cce1d916",
"md5": "62473a623a4fd3d012014aaebf17182e",
"sha256": "aa946c8327e22ced28e7cef508a334673abc42064ec85f02d005ba1785ea4cec"
},
"downloads": -1,
"filename": "nvidia_nccl_cu12-2.23.4-py3-none-manylinux2014_aarch64.whl",
"has_sig": false,
"md5_digest": "62473a623a4fd3d012014aaebf17182e",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3",
"size": 198953892,
"upload_time": "2024-09-11T23:29:56",
"upload_time_iso_8601": "2024-09-11T23:29:56.861605Z",
"url": "https://files.pythonhosted.org/packages/c8/3a/0112397396dec37ffc8edd7836d48261b4d14ca60ec8ed7bc857cce1d916/nvidia_nccl_cu12-2.23.4-py3-none-manylinux2014_aarch64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "ed1f6482380ec8dcec4894e7503490fc536d846b0d59694acad9cf99f27d0e7d",
"md5": "70ecab48cc227313937c01b936cdae88",
"sha256": "b097258d9aab2fa9f686e33c6fe40ae57b27df60cedbd15d139701bb5509e0c1"
},
"downloads": -1,
"filename": "nvidia_nccl_cu12-2.23.4-py3-none-manylinux2014_x86_64.whl",
"has_sig": false,
"md5_digest": "70ecab48cc227313937c01b936cdae88",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3",
"size": 198954603,
"upload_time": "2024-09-11T23:30:16",
"upload_time_iso_8601": "2024-09-11T23:30:16.650663Z",
"url": "https://files.pythonhosted.org/packages/ed/1f/6482380ec8dcec4894e7503490fc536d846b0d59694acad9cf99f27d0e7d/nvidia_nccl_cu12-2.23.4-py3-none-manylinux2014_x86_64.whl",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-09-11 23:29:56",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "nvidia-nccl-cu12"
}