Coral TPU MINI PCIE Module

This is Coral TPU MINI PCIE Module. The Coral Mini PCIe Accelerator is a Half-Mini PCIe card that brings the Edge TPU ML accelerator to existing systems and products.
The Edge TPU is a small ASIC designed by Google that accelerates TensorFlow Lite models in a power efficient manner: it’s capable of performing 4 trillion operations per second (4 TOPS), using 2 watts of power—that’s 2 TOPS per watt. For example, one Edge TPU can execute state-of-the-art mobile vision models such as MobileNet v2 at almost 400 frames per second. This on-device ML processing reduces latency, increases data privacy, and removes the need for a constant internet connection.
The Half-Mini PCIe form-factor allows you to add local ML acceleration to products such as embedded platforms, mini-PCs, and industrial gateways that have an available Mini PCIe slot.

Note: Refer to datasheet in the ATTACHMENTS section for more info. regd. the product.

Features:

1. Easy to use
2. Good quality product
3. Google Edge TPU ML accelerator
   • 4 TOPS total peak performance (int8)
   • 2 TOPS per watt
4. Integrated power management
5. PCIe Gen2 x1 interface
6. Standard Half-Mini PCIe card
7. Operating temp: -20 to +85 °C

Package Includes:

1 x Coral TPU MINI PCIE Module

For more info., click below.

Application notes

• Get started with the M.2 or PCIe Accelerator
• Manage the PCIe module temperature

Software guides

• Model compatibility on the Edge TPU
• Edge TPU inferencing overview
• Run multiple models with multiple Edge TPUs
• Pipeline a model with multiple Edge TPUs

API references

• PyCoral API (Python)
• Libcoral API (C++)
• Libedgetpu API (C++)

Downloads link

• Edge TPU compiler
• Pre-compiled models
• All software downloads