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{{short description|Open standard for parallel computing}}
 
{{lowercase title}}
{{otheruses|OneAPI (disambiguation)}}
oneAPI is a cross-industry initiative for an open, standards-based unified programming model that creates a common developer experience across compute accelerator architectures. Its objective is to deliver an efficient, performant programming model that eliminates the need for developers to maintain separate code bases, multiple programming languages, and different tools and workflows for each architecture.
{{Infobox software
| name = oneAPI
| logo = OneAPI-rgb-3000.png
| logo_caption =
| latest_release_date = {{start date and age|2020|11|13}}
| operating_system = [[Cross-platform]]
| platform = Cross-platform
| genre = [[Open-source software|Open-source]] [[Formal specification|software specification]] for parallel programming
| repo = {{URL|https://github.com/oneapi-src}}
| website = {{official URL}}
}}
 
'''oneAPI''' is an [[open standard]], adopted by Intel,{{sfn|Fortenberry|Tomov|2022|p=22}} for a unified [[application programming interface]] (API) intended to be used across different computing [[Hardware acceleration|accelerator]] ([[coprocessor]]) architectures, including [[GPU]]s, [[AI accelerator]]s and [[field-programmable gate array]]s. It is intended to eliminate the need for developers to maintain separate code bases, multiple programming languages, tools, and workflows for each architecture.<ref>{{Cite web|url=https://www.hpcwire.com/2019/12/09/intel-expands-its-silicon-portfolio-and-oneapi-software-initiative-for-next-generation-hpc/|title=Intel Expands its Silicon Portfolio, and oneAPI Software Initiative for Next-Generation HPC|date=2019-12-09|website=HPCwire|language=en-US|access-date=2020-02-11}}</ref><ref>{{Cite web|url=https://www.hpcwire.com/2019/11/17/intel-debuts-new-gpu-ponte-vecchio-and-outlines-aspirations-for-oneapi/|title=Intel Debuts New GPU – Ponte Vecchio – and Outlines Aspirations for oneAPI|date=2019-11-18|website=HPCwire|language=en-US|access-date=2020-02-11}}</ref><ref>{{Cite web|url=https://www.extremetech.com/computing/302284-sc19-intel-unveils-new-gpu-stack-oneapi-development-effort|title=SC19: Intel Unveils New GPU Stack, oneAPI Development Effort - ExtremeTech|website=www.extremetech.com|access-date=2020-02-11}}</ref><ref>{{Cite web|url=https://www.servethehome.com/intel-one-api-to-rule-them-all-is-much-needed/|title=Intel One API to Rule Them All Is Much Needed to Expand TAM|last=Kennedy|first=Patrick|date=2018-12-24|website=ServeTheHome|language=en-US|access-date=2020-02-11}}</ref>
 
oneAPI competes with other GPU computing stacks: [[CUDA]] by [[Nvidia]] and [[ROCm]] by [[AMD]].
 
== The oneAPI Specification ==
The oneAPI specification<ref>{{Cite web|url=https://spec.oneapi.com/oneAPI/|title=The oneAPI Specification|last=|first=|date=|website=oneAPI|url-status=live|archive-url=|archive-date=|access-date=}}</ref> extends existing developer programming models to enable multiple hardware architectures through a data-parallel language, a set of library APIs, and a low-level hardware interface to support cross-architecture programming. It builds upon industry standards and provides an open, cross-platform developer stack.<ref name="spec">{{cite web |url=https://www.oneapi.io/spec/ |title=oneAPI Specification |last= |first= |date= |website=oneAPI |archive-url= |archive-date= |access-date=}}</ref><ref>{{Cite web|date=2021-03-23|title=Preparing for the Arrival of Intel's Discrete High-Performance GPUs|url=https://www.hpcwire.com/2021/03/23/preparing-for-the-arrival-of-intels-discrete-high-performance-gpus/|access-date=2021-03-29|website=HPCwire|language=en-US}}</ref>
 
== The Language – Data Parallel C++ ==
[[Intel_C%2B%2B_Compiler|DPC++]]<ref>{{Cite web|url=https://www.apress.com/gp/data-parallel-c-advanced-chapters-just-released/17382670|title=Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems Using C++ and SYCL|last=|first=|date=|website=Apress|url-status=live|archive-url=|archive-date=|access-date=}}</ref><ref>{{Cite isweb|url=https://insidebigdata.com/2019/12/16/heterogeneous-computing-programming-oneapi-and-data-parallel-c/|title=Heterogeneous anComputing open,Programming: crossoneAPI and Data Parallel C++|last=Team|first=Editorial|date=2019-architecture12-16|website=insideBIGDATA|language=en-US|access-date=2020-02-11}}</ref> is a programming language implementation of oneAPI, built upon the [[ISO C++]] and [[Khronos Group]] [[SYCL]] standards.<ref>{{Cite web|url=https://www.khronos.org/news/permalink/intels-one-api-project-incorporates-sycl|title=The Khronos Group|date=2020-02-11|website=The Khronos Group|language=en|access-date=2020-02-11}}</ref> DPC++ extendsis thesean standardsimplementation of SYCL with explicitextensions parallelthat constructsare likeproposed sub-groupsfor andinclusion in future revisions of the SYCL standard, including: unified shared memory, offloadgroup interfacesalgorithms, toand supportsub-groups.<ref>{{Cite aweb|date=2020-06-30|title=Khronos broadSteps rangeTowards Widespread Deployment of computingSYCL architectureswith andRelease processorsof SYCL 2020 Provisional Specification|url=https://www.khronos.org/news/press/khronos-releases-sycl-2020-provisional-specification|access-date=2020-07-06|website=The Khronos Group|language=en}}</ref><ref>{{Cite web|last=staff|date=2020-06-30|title=New, includingOpen [[CPU]]sDPC++ Extensions Complement SYCL and acceleratorsC++|url=https://insidehpc.com/2020/06/new-open-dpc-extensions-complement-sycl-and-c/|access-date=2020-07-06|website=insideHPC|language=en-US}}</ref><ref>{{Cite web|date=2021-02-09|title=SYCL Extensions2020 areLaunches contributedwith backNew toName, standardsNew bodiesFeatures, and High Ambition|url=https://www.hpcwire.com/2021/02/09/sycl-2020-launches-new-name-new-features/|access-date=2021-02-16|website=HPCwire|language=en-US}}</ref>
 
== The oneAPI Libraries ==
The set of APIs<ref>{{Cite web|urlname=https://www.oneapi.com/"spec/|title=oneAPI" specification elements|last=|first=|date=|website=oneAPI|url-status=live|archive-url=|archive-date=|access-date=}}</ref> spans several domains that benefit from acceleration, including an interface for deep learning; general libraries for linear algebra, deep mathlearning, videomachine learning, and mediavideo processing;, and others.
{| class="wikitable"
!'''Library Name'''
Line 21 ⟶ 36:
|Algorithms and functions to speed DPC++ kernel programming
|-
|[[Math Kernel Library|oneAPI Math Kernel Library]]
|oneMKL
|Math routines including matrix algebra, FFT, and vector math
|-
|[[Data Analytics Library|oneAPI Data Analytics Library]]
|oneDAL
|Machine learning and data analytics functions
Line 37 ⟶ 52:
|Communication patterns for distributed deep learning
|-
|[[Threading Building Blocks|oneAPI Threading Building Blocks]]
|oneTBB
|Threading and memory management template library
Line 46 ⟶ 61:
|}
 
The [[source code]] of parts of the above libraries is available on GitHub.<ref>{{cite web |title=oneAPI-SRC |url=https://github.com/oneapi-src |website=GitHub |language=en}}</ref>
== The Hardware Abstraction Layer ==▼
 
oneAPI Level Zero, the low-level hardware interface, defines a set of capabilities and services that a hardware accelerator needs to interface with compiler runtimes and other developer tools.
The oneAPI documentation also lists the "Level Zero" API defining the low-level direct-to-metal interfaces and a set of [[Ray tracing (graphics)|ray tracing]] components with its own APIs.<ref name="spec" />
 
▲== The Hardware Abstractionabstraction Layerlayer ==
oneAPI Level Zero,<ref>{{Cite web|url=https://www.tomshardware.com/news/intel-releases-bare-metal-oneapi-level-zero-specification|title=Intel Releases Bare-Metal oneAPI Level Zero Specification|last=Verheyde 2019-12-08T16:11:19Z|first=Arne|website=Tom's Hardware|date=8 December 2019 |language=en|access-date=2020-02-11}}</ref><ref>{{Cite web|url=https://www.phoronix.com/scan.php?page=news_item&px=Intel-oneAPI-Level-Zero|title=Intel's Compute Runtime Adds oneAPI Level Zero Support - Phoronix|website=www.phoronix.com|access-date=2020-03-10}}</ref><ref>{{Cite web|url=https://www.phoronix.com/scan.php?page=article&item=intel-level-zero&num=1|title=Initial Benchmarks With Intel oneAPI Level Zero Performance - Phoronix|website=www.phoronix.com|access-date=2020-04-13}}</ref> the low-level hardware interface, defines a set of capabilities and services that a hardware accelerator needs to interface with compiler runtimes and other developer tools.
 
== Implementations ==
[[Intel]] has released oneAPI production toolkits that implement the specification and add CUDA code migration, analysis, and debug tools.<ref>{{Cite news|date=2020-11-11|title=Intel Champions XPU Vision With oneAPI, Data Center GPUs - SDxCentral|language=en-US|work=SDxCentral|url=https://www.sdxcentral.com/articles/news/intel-champions-xpu-vision-with-oneapi-data-center-gpus/2020/11/|access-date=2020-11-11}}</ref><ref>{{Cite web|date=2020-11-11|title=Intel Debuts oneAPI Gold and Provides More Details on GPU Roadmap|url=https://www.hpcwire.com/2020/11/11/intel-debuts-oneapi-gold-and-provides-more-details-on-gpu-roadmap/|access-date=2020-11-11|website=HPCwire|language=en-US}}</ref><ref>{{Cite web|last=Moorhead|first=Patrick|title=Intel Announces Gold Release Of OneAPI Toolkits And New Intel Server GPU|url=https://www.forbes.com/sites/patrickmoorhead/2020/12/02/intel-announces-gold-release-of-oneapi-toolkits-and-new-intel-server-gpu/|access-date=2020-12-08|website=Forbes|language=en}}</ref> These include the [[Intel C++ compiler|Intel oneAPI DPC++/C++ Compiler]],<ref>{{Cite web|title=Data Parallel C++ for Cross-Architecture Applications|url=https://www.intel.com/content/www/us/en/develop/tools/oneapi/components/dpc-compiler.html|access-date=2021-10-07|website=Intel|language=en}}</ref> [[Intel Fortran Compiler]], [[VTune|Intel VTune]] Profiler<ref>{{Cite web|title=Fix Performance Bottlenecks with Intel® VTune™ Profiler|url=https://www.intel.com/content/www/us/en/develop/tools/oneapi/components/vtune-profiler.html|access-date=2021-10-07|website=Intel|language=en}}</ref> and multiple performance libraries.
[[Intel]] has released a oneAPI Beta Product<ref>{{Cite web|url=https://software.intel.com/en-us/oneapi|title=Intel oneAPI Product|last=|first=|date=|website=Intel oneAPI Toolkits|url-status=live|archive-url=|archive-date=|access-date=}}</ref> that implements the specification and adds migration, analysis, and debug tools.
 
[[Codeplay]] ishas workingreleased onan a to-be-open-source layer<ref>{{Cite web|url=https://www.hpcwire.com/2020/02/04/codeplay-open-sources-a-version-of-computecpp-for-nvidia-gpus/|title=Codeplay Open Sources a Version of DPC++ for Nvidia GPUs|date=2020-02-05|website=HPCwire|language=en-US|access-date=2020-02-12}}</ref><ref>{{Cite web|url=https://www.phoronix.com/scan.php?page=news_item&px=Intel-oneAPI-DPC-SYCL-NVIDIA-CU|title=Intel's oneAPI / DPC++ / SYCL Will Run Atop NVIDIA GPUs With Open-Source Layer - Phoronix|website=www.phoronix.com|access-date=2019-12-06}}</ref><ref>{{Cite web|url=https://www.codeplay.com/portal/02-03-20-codeplay-contribution-to-dpcpp-brings-sycl-support-for-nvidia-gpus|title=Codeplay - Codeplay contribution to DPC++ brings SYCL support for NVIDIA GPUs|website=www.codeplay.com|access-date=2020-02-11}}</ref> to allow oneAPI and [[SYCL]] |SYCL/ Data Parallel CDPC++]] to run atop [[Nvidia]] [[GPU]]s via [[CUDA]].
 
[[Heidelberg University|University of Heidelberg]] has developed a SYCL/DPC++ implementation for both AMD and Nvidia GPUs.<ref>{{Cite web|last=Salter|first=Jim|date=2020-09-30|title=Intel, Heidelberg University team up to bring Radeon GPU support to AI|url=https://arstechnica.com/gadgets/2020/09/intel-heidelberg-university-team-up-to-bring-radeon-gpu-support-to-ai/|access-date=2021-10-07|website=Ars Technica|language=en-us}}</ref>
== External links ==▼
 
[[Huawei]] released a DPC++ compiler for their Ascend AI Chipset<ref>{{Citation|title=Extending DPC++ with Support for Huawei Ascend AI Chipset| date=27 April 2021 |url=https://www.youtube.com/watch?v=7foee4_QkbU|language=en|access-date=2021-10-07}}</ref>
* [https://www.apress.com/gp/data-parallel-c-advanced-chapters-just-released/17382670 Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems Using C++ and SYCL]
 
* [https://www.phoronix.com/scan.php?page=news_item&px=Intel-oneAPI-DPC-SYCL-NVIDIA-CU oneAPI / DPC++ / SYCL Will Run Atop NVIDIA GPUs]
[[Fujitsu]] has created an open-source [[ARM architecture|ARM]] version of the oneAPI Deep Neural Network Library (oneDNN)<ref>{{Cite web|last=fltech|date= 19 November 2020|title=A Deep Dive into a Deep Learning Library for the A64FX Fugaku CPU - The Development Story in the Developer's Own Words|url=https://blog.fltech.dev/entry/2020/11/19/fugaku-onednn-deep-dive-en|access-date=2021-02-10|website=fltech - 富士通研究所の技術ブログ|language=ja}}</ref> for their [[Fugaku (supercomputer)|Fugaku CPU]].
*[https://www.codeplay.com/portal/12-16-19-bringing-nvidia-gpu-support-to-sycl-developers Bringing Nvidia GPU support to SYCL developers]▼
 
* [https://www.hpcwire.com/2019/11/17/intel-debuts-new-gpu-ponte-vecchio-and-outlines-aspirations-for-oneapi/ Intel Debuts New GPU – Ponte Vecchio – and Outlines Aspirations for oneAPI]
== Unified Acceleration Foundation (UXL) and the future for oneAPI{{anchor|UXL}} ==
* [https://www.oneapi.com/ oneAPI Industry Specification]
 
* [https://software.intel.com/en-us/oneapi Intel oneAPI Product]
Unified Acceleration Foundation (UXL) is a new technology consortium that are working on the continuation of the OneAPI initiative, with the goal to create a new open standard accelerator software ecosystem, related open standards and specification projects through Working Groups and Special Interest Groups (SIGs). The goal will compete with Nvidia's CUDA. The main companies behind it are Intel, Google, ARM, Qualcomm, Samsung, Imagination, and VMware.<ref>{{Cite web |title=Exclusive: Behind the plot to break Nvidia's grip on AI by targeting software |website=[[Reuters]] |url=https://www.reuters.com/technology/behind-plot-break-nvidias-grip-ai-by-targeting-software-2024-03-25/ |access-date=2024-04-05}}</ref>
*[https://www.khronos.org/news/tags/tag/sycl Sycl tagged news]
 
==References==
{{reflist}}
<references />
 
== Sources ==
* {{cite conference |url= https://icl.utk.edu/files/publications/2022/icl-utk-1616-2022.pdf |title=Extending MAGMA Portability with OneAPI |last1=Fortenberry |first1=Anna |last2=Tomov |first2=Stanimire |date=2022 |publisher=[[IEEE]] |book-title= |pages=22–31 |___location= |conference=2022 Workshop on Accelerator Programming Using Directives (WACCPD) |id=}} .
 
▲== External links ==
* {{official website}}
* {{GitHub|oneapi-src|oneAPI}}
▲* [https://www.codeplay.com/portal/12-16-19-bringing-nvidia-gpu-support-to-sycl-developers Bringing Nvidia GPU support to SYCL developers]
* {{cite book |display-authors= 1 |first1= James |last1= Reinders |first2= Ben |last2= Ashbaugh |first3= James |last3= Brodman |first4= Michael |last4= Kinsner |first5= John |last5= Pennycook |first6= Xinmin |last6= Tian |url= https://link.springer.com/book/10.1007/978-1-4842-5574-2 |title= Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL |publisher= Springer |isbn= 978-1-4842-5574-2 |doi= 10.1007/978-1-4842-5574-2 |series= Open Access Book |year= 2021 |s2cid= 226231933 }}
* [https://developer.codeplay.com/products/oneapi/nvidia/2025.1.0/guides/index oneAPI for NVIDIA GPUs 2025.1.0]
* [https://developer.codeplay.com/products/oneapi/amd/2025.1.0/guides/index oneAPI for AMD GPUs 2025.1.0]
 
[[Category:ComputerApplication programming interfaces]]
[[Category:Cross-platform software]]
[[Category:Intel software]]
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