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-cu13",
"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": null,
"summary": "NVIDIA Collective Communication Library (NCCL) Runtime",
"version": "2.28.7",
"project_urls": {
"Homepage": "https://developer.nvidia.com/cuda-zone"
},
"split_keywords": [
"cuda",
" nvidia",
" runtime",
" machine learning",
" deep learning"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "e289b24132be74a263e890bb3f19bafc0132f7149699c7300f5d71b60eac208a",
"md5": "c60bf7a13ab42485d4ff41e881ddb6ec",
"sha256": "7b386e887830666e6fce17287a00173cc78a7e9abf158138b99a45f59e9904e2"
},
"downloads": -1,
"filename": "nvidia_nccl_cu13-2.28.7-py3-none-manylinux_2_18_aarch64.whl",
"has_sig": false,
"md5_digest": "c60bf7a13ab42485d4ff41e881ddb6ec",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3",
"size": 196534578,
"upload_time": "2025-10-21T23:16:05",
"upload_time_iso_8601": "2025-10-21T23:16:05.835578Z",
"url": "https://files.pythonhosted.org/packages/e2/89/b24132be74a263e890bb3f19bafc0132f7149699c7300f5d71b60eac208a/nvidia_nccl_cu13-2.28.7-py3-none-manylinux_2_18_aarch64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "0e00677ca131172fea165172dfc0f8363181a651605e066b5ca9cf8c1eb2f1b7",
"md5": "6cff270b398c5bef5eb839307ebc5495",
"sha256": "f9988ff615aa2e21dffc606a8e5861fe41f4140b4540856a780009c4b1c3626f"
},
"downloads": -1,
"filename": "nvidia_nccl_cu13-2.28.7-py3-none-manylinux_2_18_x86_64.whl",
"has_sig": false,
"md5_digest": "6cff270b398c5bef5eb839307ebc5495",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3",
"size": 196467404,
"upload_time": "2025-10-21T23:16:19",
"upload_time_iso_8601": "2025-10-21T23:16:19.044581Z",
"url": "https://files.pythonhosted.org/packages/0e/00/677ca131172fea165172dfc0f8363181a651605e066b5ca9cf8c1eb2f1b7/nvidia_nccl_cu13-2.28.7-py3-none-manylinux_2_18_x86_64.whl",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-10-21 23:16:05",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "nvidia-nccl-cu13"
}
JSON