OneAPI (compute acceleration): Difference between revisions
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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> |
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> |
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Huawei released a DPC++ compiler for their Ascend AI Chipset<ref>{{Citation|title=Extending DPC++ with Support for Huawei Ascend AI Chipset|url=https://www.youtube.com/watch?v=7foee4_QkbU|language=en|access-date=2021-10-07}}</ref> |
[[Huawei]] released a DPC++ compiler for their Ascend AI Chipset<ref>{{Citation|title=Extending DPC++ with Support for Huawei Ascend AI Chipset|url=https://www.youtube.com/watch?v=7foee4_QkbU|language=en|access-date=2021-10-07}}</ref> |
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[[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]]. |
[[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]]. |
Revision as of 22:48, 11 March 2023
A major contributor to this article appears to have a close connection with its subject. (October 2021) |
Repository | github |
---|---|
Operating system | Cross-platform |
Platform | Cross-platform |
Type | Open-source software specification for parallel programming |
Website | www |
oneAPI is an open standard for a unified application programming interface intended to be used across different compute accelerator (coprocessor) architectures, including GPUs, AI accelerators and field-programmable gate arrays. It is intended to eliminate the need for developers to maintain separate code bases, multiple programming languages, and different tools and workflows for each architecture.[1][2][3][4]
The oneAPI specification
The oneAPI specification 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.[5][6]
Data Parallel C++
DPC++[7][8] is an open, cross-architecture language built upon the ISO C++ and Khronos Group SYCL standards.[9] DPC++ is an implementation of SYCL with extensions that are proposed for inclusion in future revisions of the SYCL standard. An example of this is the contribution of unified shared memory, group algorithms and sub-groups to SYCL 2020.[10][11][12]
oneAPI libraries
The set of APIs[5] spans several domains that benefit from acceleration, including libraries for linear algebra math, deep learning, machine learning, video processing, and others.
Library Name | Short
Name |
Description |
---|---|---|
oneAPI DPC++ Library | oneDPL | Algorithms and functions to speed DPC++ kernel programming |
oneAPI Math Kernel Library | oneMKL | Math routines including matrix algebra, FFT, and vector math |
oneAPI Data Analytics Library | oneDAL | Machine learning and data analytics functions |
oneAPI Deep Neural Network Library | oneDNN | Neural networks functions for deep learning training and inference |
oneAPI Collective Communications Library | oneCCL | Communication patterns for distributed deep learning |
oneAPI Threading Building Blocks | oneTBB | Threading and memory management template library |
oneAPI Video Processing Library | oneVPL | Real-time video encode, decode, transcode, and processing |
The source code of most implementations of the above libraries is available on GitHub.[13]
The oneAPI documentation also lists the "Level Zero" API defining the low-level direct-to-metal interfaces and a set or ray tracing components with its own APIs.[5]
Hardware abstraction layer
oneAPI Level Zero,[14][15][16] 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 production quality oneAPI toolkits that implement the specification and add CUDA code migration, analysis, and debug tools.[17][18][19] These include the Intel oneAPI DPC++/C++ Compiler,[20] Intel Fortran Compiler, Intel VTune Profiler[21] and multiple performance libraries.
Codeplay has released an open-source layer[22][23][24] to allow oneAPI and SYCL/DPC++ to run atop Nvidia GPUs via CUDA.
University of Heidelberg has developed a SYCL/DPC++ implementation for both AMD and Nvidia GPUs.[25]
Huawei released a DPC++ compiler for their Ascend AI Chipset[26]
Fujitsu has created an open-source ARM version of the oneAPI Deep Neural Network Library (oneDNN)[27] for their Fugaku CPU.
References
- ^ "Intel Expands its Silicon Portfolio, and oneAPI Software Initiative for Next-Generation HPC". HPCwire. 2019-12-09. Retrieved 2020-02-11.
- ^ "Intel Debuts New GPU – Ponte Vecchio – and Outlines Aspirations for oneAPI". HPCwire. 2019-11-18. Retrieved 2020-02-11.
- ^ "SC19: Intel Unveils New GPU Stack, oneAPI Development Effort - ExtremeTech". www.extremetech.com. Retrieved 2020-02-11.
- ^ Kennedy, Patrick (2018-12-24). "Intel One API to Rule Them All Is Much Needed to Expand TAM". ServeTheHome. Retrieved 2020-02-11.
- ^ a b c "oneAPI Specification". oneAPI.
{{cite web}}
: CS1 maint: url-status (link) - ^ "Preparing for the Arrival of Intel's Discrete High-Performance GPUs". HPCwire. 2021-03-23. Retrieved 2021-03-29.
- ^ "Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems Using C++ and SYCL". Apress.
{{cite web}}
: CS1 maint: url-status (link) - ^ Team, Editorial (2019-12-16). "Heterogeneous Computing Programming: oneAPI and Data Parallel C++". insideBIGDATA. Retrieved 2020-02-11.
- ^ "The Khronos Group". The Khronos Group. 2020-02-11. Retrieved 2020-02-11.
- ^ "Khronos Steps Towards Widespread Deployment of SYCL with Release of SYCL 2020 Provisional Specification". The Khronos Group. 2020-06-30. Retrieved 2020-07-06.
- ^ staff (2020-06-30). "New, Open DPC++ Extensions Complement SYCL and C++". insideHPC. Retrieved 2020-07-06.
- ^ "SYCL 2020 Launches with New Name, New Features, and High Ambition". HPCwire. 2021-02-09. Retrieved 2021-02-16.
- ^ "oneAPI-SRC". GitHub.
- ^ Verheyde 2019-12-08T16:11:19Z, Arne. "Intel Releases Bare-Metal oneAPI Level Zero Specification". Tom's Hardware. Retrieved 2020-02-11.
{{cite web}}
: CS1 maint: numeric names: authors list (link) - ^ "Intel's Compute Runtime Adds oneAPI Level Zero Support - Phoronix". www.phoronix.com. Retrieved 2020-03-10.
- ^ "Initial Benchmarks With Intel oneAPI Level Zero Performance - Phoronix". www.phoronix.com. Retrieved 2020-04-13.
- ^ "Intel Champions XPU Vision With oneAPI, Data Center GPUs - SDxCentral". SDxCentral. 2020-11-11. Retrieved 2020-11-11.
- ^ "Intel Debuts oneAPI Gold and Provides More Details on GPU Roadmap". HPCwire. 2020-11-11. Retrieved 2020-11-11.
- ^ Moorhead, Patrick. "Intel Announces Gold Release Of OneAPI Toolkits And New Intel Server GPU". Forbes. Retrieved 2020-12-08.
- ^ "Data Parallel C++ for Cross-Architecture Applications". Intel. Retrieved 2021-10-07.
- ^ "Fix Performance Bottlenecks with Intel® VTune™ Profiler". Intel. Retrieved 2021-10-07.
- ^ "Codeplay Open Sources a Version of DPC++ for Nvidia GPUs". HPCwire. 2020-02-05. Retrieved 2020-02-12.
- ^ "Intel's oneAPI / DPC++ / SYCL Will Run Atop NVIDIA GPUs With Open-Source Layer - Phoronix". www.phoronix.com. Retrieved 2019-12-06.
- ^ "Codeplay - Codeplay contribution to DPC++ brings SYCL support for NVIDIA GPUs". www.codeplay.com. Retrieved 2020-02-11.
- ^ Salter, Jim (2020-09-30). "Intel, Heidelberg University team up to bring Radeon GPU support to AI". Ars Technica. Retrieved 2021-10-07.
- ^ Extending DPC++ with Support for Huawei Ascend AI Chipset, retrieved 2021-10-07
- ^ fltech. "A Deep Dive into a Deep Learning Library for the A64FX Fugaku CPU - The Development Story in the Developer's Own Words". fltech - 富士通研究所の技術ブログ (in Japanese). Retrieved 2021-02-10.
External links
- oneAPI Industry Specification
- Intel oneAPI Product
- Bringing Nvidia GPU support to SYCL developers
- Reinders, James; et al. (2021). Data Parallel C++: Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL. Open Access Book. Springer. doi:10.1007/978-1-4842-5574-2. ISBN 978-1-4842-5574-2. S2CID 226231933.
- oneapi-src on GitHub