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{{lowercase title}}▼
{{short description|Open standard for parallel computing}}
▲{{lowercase title}}
{{otheruses|OneAPI (disambiguation)}}▼
{{Infobox software
| name = oneAPI
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| website = {{official URL}}
}}
▲{{otheruses|OneAPI (disambiguation)}}
'''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
== Specification ==
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== Hardware abstraction layer ==
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 ==
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[[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>
[[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>
[[Fujitsu]] has created an open-source [[ARM architecture|ARM]] version of the oneAPI Deep Neural Network Library (oneDNN)<ref>{{Cite web|last=fltech|date= |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]].▼
▲oneAPI competes with other GPU computing stacks: [CUDA|CUDA by NVIDIA]] and [[ROCm|ROCm by AMD]].
▲[[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]].
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,
==References==
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== External links ==
* {{official website
*
* [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:Application programming interfaces]]
[[Category:Cross-platform software]]
[[Category:Intel software]]
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