Modzy Edge provides a way for machine learning models to run "at the edge" on hardware such as remove servers and edge devices.

How does Modzy Edge Work?

When you connect your edge device to Modzy, the following things happen:

  1. It downloads a copy of Modzy Core to your edge device. This small executable provides an API interface for any models you deploy to the edge. You can learn more about the Modzy Edge API here.
  2. It registers your device with Modzy and associates it with a device group
  3. It automatically downloads any models you've added to your device group and starts running them on your edge device

Minimum Device Requirements

To use Modzy Edge on an edge device, that device must meet some minimum hardware requirements. These requirements are typically easy to meet in the cloud, or on-prem, but Modzy Edge also works with many small form-factor devices.

Operating SystemLinux
CPURequires an ARM 32-bit, ARM 64-bit, or x86 (AMD or Intel) 64-bit processor, with at least 2 cores
RAM2+ GiB of RAM is recommended, but more may be required for running larger models or multiple models at once
GPUNot required, but Modzy Edge supports NVIDIA GPUs
TPUNot required and not yet supported (though models will still run on a CPU)
Device Storage16+ GiB of storage is recommended, but more may be required for storing model results
DependenciesDocker v20.10.x or newer

Validated Small Form-factor Devices

Modzy Edge has been tested on the following small form-factor edge devices

  • Nvidia Jetson Nano 4GB
  • Raspberry Pi 3 Model B+

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