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If I have several connected Myriad X VPUs, how can I set specified Device_id in C++?
- In general, if I want to use multi-stick computation from one application, should I select different VPU device_id's and create network?
- Or should I just create 2 Networks and they will be allocated on two difference VPUs?
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Hi ABoch5,
1. In general, if I want to use multi-stick computation from one application, should I select different VPU device_id's and create network?
No, the OpenVINO tooklit application will automatically manage the workload for multiple NCS devices, so there is no need to select different VPU device_id's. You can just make one PlugIn instance that will manage all the MYRIAD devices on your system.
2. Or should I just create 2 Networks and they will be allocated on two difference VPUs?
Yes, for maximum performance, you should create an ExecutableNetwork instance for each device. Note: it is not possible to tie each network directly to each device.
Take a look at the "Multiple NCS Devices" section of this webpage for more information: https://software.intel.com/en-us/articles/transitioning-from-intel-movidius-neural-compute-sdk-to-openvino-toolkit
Regards,
Aroop
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Hi ABoch5,
1. In general, if I want to use multi-stick computation from one application, should I select different VPU device_id's and create network?
No, the OpenVINO tooklit application will automatically manage the workload for multiple NCS devices, so there is no need to select different VPU device_id's. You can just make one PlugIn instance that will manage all the MYRIAD devices on your system.
2. Or should I just create 2 Networks and they will be allocated on two difference VPUs?
Yes, for maximum performance, you should create an ExecutableNetwork instance for each device. Note: it is not possible to tie each network directly to each device.
Take a look at the "Multiple NCS Devices" section of this webpage for more information: https://software.intel.com/en-us/articles/transitioning-from-intel-movidius-neural-compute-sdk-to-openvino-toolkit
Regards,
Aroop
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Thanks!
I changed this code: https://github.com/opencv/open_model_zoo/blob/e458c1f0407d0303e36be4828bb963a67d6d050a/demos/object_detection_demo_yolov3_async/main.cpp#L287-L293
ExecutableNetwork network = plugin.LoadNetwork(netReader.getNetwork(), {});
// -----------------------------------------------------------------------------------------------------
// --------------------------- 5. Creating infer request -----------------------------------------------
InferRequest::Ptr async_infer_request_next = network.CreateInferRequestPtr();
InferRequest::Ptr async_infer_request_curr = network.CreateInferRequestPtr();
to this code:
ExecutableNetwork network = plugin.LoadNetwork(netReader.getNetwork(), {});
ExecutableNetwork network2 = plugin.LoadNetwork(netReader.getNetwork(), {});
// -----------------------------------------------------------------------------------------------------
// --------------------------- 5. Creating infer request -----------------------------------------------
InferRequest::Ptr async_infer_request_next = network2.CreateInferRequestPtr();
InferRequest::Ptr async_infer_request_curr = network.CreateInferRequestPtr();
Then run application object_detection_demo_yolov3_async and press TAB for async execution.
But it did not speed up the execution.
How can I see usage (in %) for each VPU?
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Hi,
I just responded to your question in the new thread you opened.
Regards,
Aroop
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