Intel® oneAPI Math Kernel Library (Intel® oneMKL) is a computing math library of highly optimized, extensively threaded routines for applications that require maximum performance. This package provides C and Data Parallel C++ (DPC++) programming language interfaces. Intel MKL C language interfaces can be called from applications written in either C or C++, as well as in any other language that can reference a C interface. Use it to optimize code for current and future generations of Intel® CPUs and GPUs.
Raw data
{
"_id": null,
"home_page": "https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html",
"name": "onemkl-sycl-stats",
"maintainer": null,
"docs_url": null,
"requires_python": null,
"maintainer_email": null,
"keywords": null,
"author": "Intel Corporation",
"author_email": "scripting@intel.com",
"download_url": null,
"platform": null,
"description": "Intel\u00ae oneAPI Math Kernel Library (Intel\u00ae oneMKL) is a computing math library of highly optimized, extensively threaded routines for applications that require maximum performance. This package provides C and Data Parallel C++ (DPC++) programming language interfaces. Intel MKL C language interfaces can be called from applications written in either C or C++, as well as in any other language that can reference a C interface. Use it to optimize code for current and future generations of Intel\u00ae CPUs and GPUs.\r\n\r\n",
"bugtrack_url": null,
"license": "Intel Simplified Software License",
"summary": "Intel\u00ae oneAPI Math Kernel Library",
"version": "2025.0.1",
"project_urls": {
"Homepage": "https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "2e76b96f30eb90c06e58980abef2594ebb264046a67d7c82ac279d173b5af5b7",
"md5": "a991948e3b53e6e8e01a4a2d7a95c61d",
"sha256": "8d1ef38921d70dc25a0058b41f4a3edbc8995cb852f82a2fd45e32c04f22e4b5"
},
"downloads": -1,
"filename": "onemkl_sycl_stats-2025.0.1-py2.py3-none-manylinux_2_28_x86_64.whl",
"has_sig": false,
"md5_digest": "a991948e3b53e6e8e01a4a2d7a95c61d",
"packagetype": "bdist_wheel",
"python_version": "py2.py3",
"requires_python": null,
"size": 6602024,
"upload_time": "2024-11-19T15:38:30",
"upload_time_iso_8601": "2024-11-19T15:38:30.023276Z",
"url": "https://files.pythonhosted.org/packages/2e/76/b96f30eb90c06e58980abef2594ebb264046a67d7c82ac279d173b5af5b7/onemkl_sycl_stats-2025.0.1-py2.py3-none-manylinux_2_28_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "88bd7b9602999df5f413f06840f23915c5f17477afc642f418f141ef602fc42f",
"md5": "bcb67c1e2076619afbc858006a2043e7",
"sha256": "2262814c41a212119a04fae18cebbfd1dff0799f4d9ec77d897ece6cde8f1cbb"
},
"downloads": -1,
"filename": "onemkl_sycl_stats-2025.0.1-py2.py3-none-win_amd64.whl",
"has_sig": false,
"md5_digest": "bcb67c1e2076619afbc858006a2043e7",
"packagetype": "bdist_wheel",
"python_version": "py2.py3",
"requires_python": null,
"size": 5794461,
"upload_time": "2024-11-19T15:37:30",
"upload_time_iso_8601": "2024-11-19T15:37:30.025041Z",
"url": "https://files.pythonhosted.org/packages/88/bd/7b9602999df5f413f06840f23915c5f17477afc642f418f141ef602fc42f/onemkl_sycl_stats-2025.0.1-py2.py3-none-win_amd64.whl",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-11-19 15:38:30",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "onemkl-sycl-stats"
}
JSON