How to Boost Performance on an Edge Device

In this tutorial, we will show you the steps needed to boost the performance of your edge device. You will need a hardware accelerator that is supported by alwaysAI – such as Intel’s Neural Compute Stick 2. You can read more about supported edge devices and how to set the engine and accelerator using the edgeiq API in our documentation.



1. Begin with a real-time detector starter app and model set

For this example, we will use the alwaysAI real-time object detector starter app, which utilizes the MobileNet SSD model. If you haven't downloaded the alwaysAI starter applications, do so now by entering 'aai get-starter-apps' from your terminal. This will download the starter applications into the current working directory. Navigate into the 'realtime_object_detector' directory.

alwaysAI App of a real-time detector starter

Here, our object detector app is detecting a potted plant in our office. Note that the inference time of the device without the accelerator is .710 seconds.

2. Change the object detection engine

To use the accelerator, change the DNN to DNN OpenVINO.

Screenshot of the change detection engine
alwaysAI Change the DNN

3. Re-deploy and run the start command

Then re-deploy the app using alwaysai app install and re-start it using the alwaysai app start command.

alwaysAI Demo_Boosting Performance on Edge device-Feb-05-2021-06-06-08-42-AM

4. Check your new inference time

Double-check the inference time from your object detector app in the Streamer on your browser.

alwaysAI Demo_Boosting Performance on Edge device-3-1

You can see that after using Intel’s Neural Compute Stick 2, the inference time has dropped to .094 seconds. That's a significant improvement for this edge device.

About alwaysAI

alwaysAI provides developers an easy-to-use platform to quickly build and deploy deep learning Computer Vision applications on “IoT” devices like cameras, drones, wearables, robots, and transportation units. The final goal of alwaysAI is giving devices  ‘intelligent sight’ and enable them to autonomously make smart decisions in real-time.

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