{"id":26452877,"url":"https://github.com/uxlfoundation/onednn","last_synced_at":"2026-03-14T13:23:38.647Z","repository":{"id":37608492,"uuid":"58414589","full_name":"uxlfoundation/oneDNN","owner":"uxlfoundation","description":"oneAPI Deep Neural Network Library (oneDNN)","archived":false,"fork":false,"pushed_at":"2025-05-12T16:43:08.000Z","size":187954,"stargazers_count":3790,"open_issues_count":129,"forks_count":1043,"subscribers_count":176,"default_branch":"main","last_synced_at":"2025-05-12T16:45:52.203Z","etag":null,"topics":["aarch64","amx","avx512","bfloat16","cpp","deep-learning","deep-neural-networks","library","oneapi","onednn","openmp","performance","sycl","tbb","vnni","x64","x86-64","xe-architecture"],"latest_commit_sha":null,"homepage":"https://uxlfoundation.org","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/uxlfoundation.png","metadata":{"files":{"readme":"README.binary.in","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":".github/CODEOWNERS","security":"SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2016-05-09T23:26:42.000Z","updated_at":"2025-05-12T16:43:11.000Z","dependencies_parsed_at":"2023-11-07T01:08:18.593Z","dependency_job_id":"bfabe4b6-a33a-48b4-8b4c-acaaee255644","html_url":"https://github.com/uxlfoundation/oneDNN","commit_stats":{"total_commits":16426,"total_committers":317,"mean_commits":51.81703470031546,"dds":0.89814927553878,"last_synced_commit":"e6cd123e00b618c5c3d1947f255a445064c81f60"},"previous_names":["intel/mkl-dnn","uxlfoundation/onednn","oneapi-src/onednn"],"tags_count":204,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uxlfoundation%2FoneDNN","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uxlfoundation%2FoneDNN/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uxlfoundation%2FoneDNN/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uxlfoundation%2FoneDNN/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/uxlfoundation","download_url":"https://codeload.github.com/uxlfoundation/oneDNN/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254041334,"owners_count":22004703,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["aarch64","amx","avx512","bfloat16","cpp","deep-learning","deep-neural-networks","library","oneapi","onednn","openmp","performance","sycl","tbb","vnni","x64","x86-64","xe-architecture"],"created_at":"2025-03-18T18:03:59.588Z","updated_at":"2026-03-14T13:23:38.633Z","avatar_url":"https://github.com/uxlfoundation.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"oneAPI Deep Neural Network Library (oneDNN)\n===========================================\n\noneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform\nperformance library of basic building blocks for deep learning applications.\noneDNN is part of oneAPI (https://oneapi.io).\nThe library is optimized for Intel(R) 64/AMD64 based processors\nand Intel Graphics.\n\noneDNN is intended for deep learning applications and framework\ndevelopers interested in improving application performance on CPUs and GPUs.\n\nThis package contains oneDNN v@PROJECT_VERSION@ (@DNNL_VERSION_HASH@).\n\nYou can find information about the latest version and release notes\nat the oneDNN Github (https://github.com/uxlfoundation/oneDNN/releases).\n\nDocumentation\n-------------\n\n* Developer guide (https://uxlfoundation.github.io/oneDNN/v@DNNL_VERSION_MAJOR@.@DNNL_VERSION_MINOR@)\n  explains the programming model, supported functionality, and implementation\n  details, and includes annotated examples.\n* API reference (https://uxlfoundation.github.io/oneDNN/v@DNNL_VERSION_MAJOR@.@DNNL_VERSION_MINOR@/modules.html)\n  provides a comprehensive reference of the library API.\n* Release Notes (https://github.com/uxlfoundation/oneDNN/releases/tag/v@DNNL_VERSION_MAJOR@.@DNNL_VERSION_MINOR@)\n  explain the new features, performance optimizations, and improvements\n  implemented in each version of oneDNN.\n\nSystem Requirements\n-------------------\n\noneDNN supports systems based on Intel 64 or AMD64 architectures.\n\nThe library is optimized for the following CPUs:\n* Intel Atom(R) processor (at least Intel SSE4.1 support is required)\n* Intel Core(TM) processor (at least Intel SSE4.1 support is required)\n* Intel Xeon(R) processor E3, E5, and E7 family (formerly Sandy Bridge,\n  Ivy Bridge, Haswell, and Broadwell)\n* Intel Xeon Scalable processor (formerly Skylake, Cascade Lake, Cooper\n  Lake, Ice Lake, Sapphire Rapids, and Emerald Rapids)\n* Intel Xeon CPU Max Series (formerly Sapphire Rapids HBM)\n* Intel Core Ultra processors (formerly Meteor Lake, Arrow Lake,\n  Lunar Lake, and Panther Lake)\n* Intel Xeon 6 processors (formerly Sierra Forest and Granite Rapids)\n* future Intel Core processor with Intel AVX10.2 instruction set support\n  (code name Nova Lake)\n* future Intel Xeon processor with Intel AVX10.2 instruction set support\n  (code name Diamond Rapids)\n\noneDNN detects the instruction set architecture (ISA) at runtime and uses\njust-in-time (JIT) code generation to deploy the code optimized\nfor the latest supported ISA. Future ISAs may have initial support in the\nlibrary disabled by default and require the use of run-time controls to enable\nthem. See CPU dispatcher control\n(https://uxlfoundation.github.io/oneDNN/dev_guide_cpu_dispatcher_control.html)\nfor more details.\n\nThe library is optimized for the following GPUs:\n* Intel discrete GPUs:\n  * Intel Iris Xe MAX Graphics (formerly DG1)\n  * Intel Arc(TM) A-Series Graphics (formerly Alchemist)\n  * Intel Data Center GPU Flex Series (formerly Arctic Sound)\n  * Intel Data Center GPU Max Series (formerly Ponte Vecchio)\n  * Intel Arc B-Series Graphics and Intel Arc Pro B-Series Graphics\n   (formerly Battlemage)\n* Intel Graphics integrated with:\n  * 11th-14th Generation Intel Core Processors\n  * Intel Graphics for Intel Core Ultra Series 1 processors (formerly Meteor Lake)\n  * Intel Graphics for Intel Core Ultra Series 2 processors (formerly Arrow Lake and Lunar Lake)\n  * Intel Graphics for Intel Core Ultra Series 3 processors (formerly Panther Lake)\n\nSupport\n-------\n\nSubmit questions, feature requests, and bug reports on the\nGitHub issues page (https://github.com/uxlfoundation/oneDNN/issues).\n\nLicense\n-------\n\noneDNN is licensed under Apache License Version 2.0. Refer to the \"LICENSE\"\nfile for the full license text and copyright notice.\n\nThis distribution includes third party software governed by separate license\nterms.\n\n3-clause BSD license:\n* Xbyak (https://github.com/herumi/xbyak)\n* Instrumentation and Tracing Technology API (ITT API)\n  (https://github.com/intel/ittapi)\n* CMake (https://github.com/Kitware/CMake)\n\nBoost Software License, Version 1.0:\n* Boost C++ Libraries (https://www.boost.org/)\n\nMIT License:\n* Intel Graphics Compute Runtime for oneAPI Level Zero and OpenCL Driver\n  (https://github.com/intel/compute-runtime)\n* Intel Graphics Compiler (https://github.com/intel/intel-graphics-compiler)\n* oneAPI Level Zero (https://github.com/oneapi-src/level-zero)\n* Intel Metrics Discovery Application Programming Interface\n  (https://github.com/intel/metrics-discovery)\n* spdlog (https://github.com/gabime/spdlog)\n\nThis third party software, even if included with the distribution of\nother software, may be governed by separate license terms, including\nwithout limitation, third party license terms, other software license\nterms, and open source software license terms. These separate license terms\ngovern your use of the third party programs as set forth in the\n\"THIRD-PARTY-PROGRAMS\" file.\n\n# Security\n\nSecurity Policy (https://github.com/uxlfoundation/oneDNN/blob/main/SECURITY.md)\noutlines our guidelines and procedures for ensuring the highest level\nof Security and trust for our users who consume oneDNN.\n\n# Trademark Information\n\nIntel, the Intel logo, Arc, Intel Atom, Intel Core, Iris,\nOpenVINO, the OpenVINO logo, Pentium, VTune, and Xeon are trademarks\nof Intel Corporation or its subsidiaries.\n\nArm and Neoverse are trademarks, or registered trademarks of Arm Ltd.\n\n\\* Other names and brands may be claimed as the property of others.\n\nMicrosoft, Windows, and the Windows logo are trademarks, or registered\ntrademarks of Microsoft Corporation in the United States and/or other\ncountries.\n\nOpenCL and the OpenCL logo are trademarks of Apple Inc. used by permission\nby Khronos.\n\n(C) Intel Corporation\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuxlfoundation%2Fonednn","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fuxlfoundation%2Fonednn","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuxlfoundation%2Fonednn/lists"}