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[[Codeplay]] has released an 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]] / Data Parallel C++ to run atop [[Nvidia]] [[GPU]]s via [[CUDA]].
[[Fujitsu]] has created an open-source [[ARM architecture|ARM]] version of the oneAPI Deep Neural Network Library (oneDNN)<ref>{{Cite web|last=fltech|date=1605805200|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 CPU.
==References==
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