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coral M.2 Accelerator datasheet

Name: coral M.2 Accelerator datasheet
Brand: SUNDAR TECHNO SOLUTIONS
Price: 5500.0 INR
Availability: InStock

Price 5500.0 INR/ Piece

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MOQ : 1 Piece

coral M.2 Accelerator datasheet Specification

Processor Main Frequency
Up to 4 TOPS (Trillion Operations Per Second)

Weight
4.6g

Processor Type
Google Edge TPU co-processor

Chipset
Edge TPU ML Accelerator

OS
Compatible with Linux, macOS, Windows, and Raspberry Pi OS

Connectivity Options
M.2 B+M Key (2242 and 2280) interface

Warranty Period
1 Year

Model Number
G650-04588-01

Hardware Security
Internal hardware cryptographic acceleration

Dimensions
22 mm x 80 mm

Input Voltage
3.3V

Operating Temperature
-40°C to 85°C

Product Name
Coral M.2 Accelerator

Supported Frameworks
TensorFlow Lite

Power Consumption
Up to 2.5W (max)

Form Factor
M.2 2242/2280 B+M key

coral M.2 Accelerator datasheet Trade Information

Minimum Order Quantity
1 Piece

Payment Terms
Cash Advance (CA)

Supply Ability
50 Pieces Per Day

Delivery Time
Days

Sample Available
No

Main Export Market(s)
Asia

Main Domestic Market
All India

Certifications
CE

coral M.2 Accelerator datasheet About

The Coral M.2 Accelerator is an M.2 module (either A+E or B+M key) 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 powerthat'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.

AI Acceleration in a Slim Form Factor

Unlock the power of AI in your projects with the Coral M.2 Accelerator, designed for seamless integration into M.2 2242 or 2280 slots. At just 4.6 grams, its compact profile makes it ideal for embedded applications and edge AI deployments, ensuring powerful inference capabilities without compromising on space or energy consumption.

Efficient and Secure Performance

Harness up to 4 TOPS with minimal power usage (up to 2.5W max) thanks to the Edge TPU ML Accelerator. Enhanced with internal hardware cryptographic acceleration, this device not only speeds up ML workloads but also ensures your data is handled securely. Versatile compatibility with TensorFlow Lite streamlines deployment for modern AI workflows.

Wide Compatibility for Developers

Whether you are using Linux, macOS, Windows, or Raspberry Pi OS, the Coral M.2 Accelerator integrates easily, speeding up your AI applications. Supported across major operating systems and development frameworks, it enables flexibility and fast prototyping, ideal for manufacturers, exporters, and suppliers in India and worldwide.

FAQ's of coral M.2 Accelerator datasheet:

Q: How do I install the Coral M.2 Accelerator into my system?

A: To install the Coral M.2 Accelerator, ensure your device supports the M.2 B+M key interface (2242 or 2280 slot). Power off your system, insert the accelerator into the appropriate M.2 slot, securely fasten it, and then boot the device. Install the latest drivers and software from Coral's official website.

Q: What frameworks and operating systems are compatible with this accelerator?

A: The Coral M.2 Accelerator is designed to support TensorFlow Lite and is compatible with Linux, macOS, Windows, and Raspberry Pi OS, making it versatile for various development setups and environments.

Q: When should I use this accelerator for my projects?

A: Utilize the Coral M.2 Accelerator for edge computing projects that require fast, efficient machine learning inferencing, particularly when space, energy consumption, and heat dissipation are critical factors-suitable for applications in industrial, automotive, and embedded AI solutions.

Q: Where can I use the Coral M.2 Accelerator in a typical workflow?

A: This accelerator is ideal for integration into embedded devices, edge servers, or desktops that require enhanced AI inferencing speed. It's well-suited for smart cameras, robotics, industrial automation, and IoT devices.

Q: What is the process for loading a machine learning model onto this accelerator?

A: First, train and convert your model to the TensorFlow Lite format. Then, deploy the model onto your host device running a supported OS. Use the provided Coral libraries or runtime APIs to load the TFLite model for inference on the Edge TPU.

Q: What are the benefits of using the Coral M.2 Accelerator for AI workloads?

A: Key benefits include high-speed AI inferencing (up to 4 TOPS), ultra-low power consumption, secure data processing via hardware cryptography, and reliable performance across harsh temperature ranges (from -40C to 85C).

Q: Is there hardware security included with the Coral M.2 Accelerator?

A: Yes, the accelerator features internal hardware cryptographic acceleration, which enhances data privacy and secure model execution for your AI applications.

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