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CORAL USB ACCELATOR 4TOPS

Name: CORAL USB ACCELATOR 4TOPS
Brand: SUNDAR TECHNO SOLUTIONS
Price: 9000.0 INR
Availability: InStock

Price 9000.0 INR/ Piece

Get a Price/Quote

MOQ : 1 Piece

CORAL USB ACCELATOR 4TOPS Specification

Processor Type
Edge TPU ML Accelerator

Processor Main Frequency
Co-processor for AI; Main frequency not applicable

Weight
20 g

Chipset
Edge TPU

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

Connectivity Options
USB 3.0 Type-A

Warranty Period
1 Year

Application
Edge AI inferencing, machine learning acceleration

Operating Environment
0°C to 50°C

Supported Frameworks
TensorFlow Lite

Device Dimensions
65 mm x 30 mm x 8 mm

Power Requirement
5V via USB port

Model Name
Coral USB Accelerator

TPU Performance
Up to 4 TOPS (Tera Operations Per Second)

Interface
USB 3.0 Type-A

CORAL USB ACCELATOR 4TOPS Trade Information

Minimum Order Quantity
1 Piece

Payment Terms
Cash Advance (CA)

Supply Ability
50 Pieces Per Day

Delivery Time
7 Days

Sample Available
No

Main Export Market(s)
Asia

Main Domestic Market
All India

Certifications
CE

About CORAL USB ACCELATOR 4TOPS

The Coral USB Accelerator adds an Edge TPU coprocessor to

your system. It includes a USB-C socket you can connect to a

host computer to perform accelerated ML inferencing.

The on-board 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.

Powerful AI Acceleration at the Edge

Empower your embedded and edge devices with the Coral USB Accelerator, built with an Edge TPU coprocessor offering up to 4 TOPS. It efficiently handles machine learning inferencing, enabling faster, real-time results without relying on a cloud connection.

Seamless Integration and Broad Compatibility

The Coral USB Accelerator features USB 3.0 Type-A connectivity, and is compatible with Linux, Windows, MacOS, and Raspberry Pi. Its straightforward integration with TensorFlow Lite enables rapid deployment in a wide range of machine learning workflows.

Efficient, Compact Design for Versatile Applications

Weighing just 20 grams and measuring 65x30x8 mm, this device fits easily into space-constrained environments. It draws minimal power directly from the USB port, making it ideal for portable and always-on AI solutions. Designed to operate between 0C and 50C, it supports various industrial and edge use cases.

FAQ's of CORAL USB ACCELATOR 4TOPS:

Q: How do I set up the Coral USB Accelerator with my system?

A: To set up the Coral USB Accelerator, simply plug it into a USB 3.0 Type-A port on your compatible device (Linux, Windows, MacOS, or Raspberry Pi). Then, install the required drivers and TensorFlow Lite runtime as guided in the official installation instructions.

Q: What benefits does the Coral USB Accelerator provide for AI inferencing?

A: The Coral USB Accelerator enables rapid, on-device AI inferencing with the Edge TPU, delivering up to 4 TOPS of performance. This reduces latency, offloads processing from the main CPU, and eliminates the need for an internet connection for local inference tasks.

Q: Which machine learning frameworks are supported by this device?

A: The Coral USB Accelerator is optimized for TensorFlow Lite, allowing you to run pre-trained TFLite models for a broad array of AI tasks on supported operating systems.

Q: When is it most advantageous to use this device?

A: This accelerator is especially useful when real-time AI inferencing is required at the edge, such as in IoT systems, smart cameras, or other devices where cloud access is limited or latency must be minimized.

Q: Where can the Coral USB Accelerator be used effectively?

A: Its compact and lightweight design makes it suitable for edge applications in industries such as manufacturing, healthcare, security, and smart home solutions-anywhere local, fast AI processing is needed.

Q: What is the process of deploying a machine learning model onto the Coral USB Accelerator?

A: First, convert your model to the TensorFlow Lite format and ensure compatibility with the Edge TPU. Load the model onto your device, connect the accelerator, and utilize TensorFlow Lite APIs to run inferences efficiently on the Edge TPU.