Coral TPU M.2 B+M Module

This is Coral TPU M.2 B+M Module. The Coral is a brand and platform developed by Google that focuses on edge AI and machine learning. It provides hardware and software components to accelerate AI and machine learning tasks on edge devices, such as IoT devices and single-board computers. TPU (Tensor Processing Unit): Google’s TPU is a specialized hardware accelerator designed for AI and machine learning workloads. TPUs are known for their high computational efficiency and are commonly used for deep learning inference tasks. M.2 B+M Module: M.2 is a form factor for expansion cards and solid-state drives (SSDs) commonly used in laptops and desktop computers. The “B+M” refers to the keying of the M.2 module, indicating the type of interface and form factor it supports.

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 M.2 form-factor allows you to add local ML acceleration to products such as embedded platforms, mini-PCs, and industrial gateways that have a compatible M.2 card slot.

Note: The actual product may vary in terms of markings and component structure. 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))
4. 2 TOPS per watt
5. Integrated power management
6. PCIe Gen2 x1 interface

Package Includes:

1 x Coral TPU M.2 B+M 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