c4eeecfec5
* Removed Intel MYRIAD plugin * Removed Intel MYIAD from CI files * Removed Intel MYRIAD from cmake folder * Removed MYRIAD, HDDL from samples * Removed MYRIAD, HDDL from scripts folder * Removed MYRIAD from bindings folder (C and Python API) * Removed MYRIAD tests * Removed MYRIAD from tests folder * Removed MYRIAD from tools folder * Removed HDDL (VAD), MYRIAD (NSC2) from documentation * Fixed build for AUTO unit tests * Fixed clang code style * Fixed comments and issues * removed MYRIAD from AUTO tests * Disabled MULTI tests in CI * Update docs/OV_Runtime_UG/auto_device_selection.md Co-authored-by: Yuan Xu <yuan1.xu@intel.com> * Update docs/get_started/get_started_demos.md Co-authored-by: Yuan Xu <yuan1.xu@intel.com> * Update docs/OV_Runtime_UG/deployment/local-distribution.md Co-authored-by: Yuan Xu <yuan1.xu@intel.com> Co-authored-by: Yuan Xu <yuan1.xu@intel.com>
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Performance Benchmarks
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openvino_docs_performance_benchmarks_openvino openvino_docs_MO_DG_Getting_Performance_Numbers
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The Intel® Distribution of OpenVINO™ toolkit helps accelerate deep learning inference across a variety of Intel® processors and accelerators.
The benchmark results below demonstrate high performance gains on several public neural networks on multiple Intel® CPUs, GPUs and GNAs covering a broad performance range. The results may be helpful when deciding which hardware is best for your applications or to plan AI workload on the Intel computing already included in your solutions.
Benchmarks are available for:
You can also test performance for your system yourself, following the guide on getting performance numbers. Performance of a particular application can also be evaluated virtually using Intel® DevCloud for the Edge. It is a remote development environment with access to Intel® hardware and the latest versions of the Intel® Distribution of the OpenVINO™ Toolkit. To learn more about it, visit the website or create an account.