Edge AI ModulesType1WV - AI Accelerator Module (featuring the Coral Edge TPU™ from Google)

The Type 1WV AI Accelerator is a multi-chip module (MCM) designed to perform high-speed inferencing for machine-learning (ML) models. It includes the Coral Edge TPU ML accelerator with integrated power control and can be connected over a PCIe Gen2 x1 or USB2 interface. The Edge TPU is a custom ASIC that accelerates TensorFlow Lite models in a power-efficient manner. It can perform 4 trillion operations per second (4 TOPS), using just 2W of power (2 TOPS/W).

Murata's design provides superior noise suppression and a simplified board layout with minimum footprint. It supports a wide range of applications including machine vision, factory automation, industrial safety, and drone control. A single 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 security, and removes the need for a constant internet connection.

Features

  • Optimized for image data classification and object detection
  • Can perform 4 trillion operations per second (4 TOPS)
  • Low power consumption (only 0.5 W per 1 TOPS)
  • Supports PCIe Gen 2 and USB 2.0 interfaces
  • Small form factor (15.0mm × 10.0mm × 1.5mm)
  • Simple toolchain for rapid development

Benchmark Comparison

A comparison of execution time for a range of TensorFlow Lite inference tasks demonstrates up to 300x speedup with the Coral Edge TPU vs a standalone embedded CPU.

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Model Development

Use pre-built models and transfer learning

The Coral SDK includes a library of pre-trained machine learning models for a variety of tasks such as image classification, object detection, semantic segmentation, pose estimation, and speech recognition. Further fine-tune these models on device with captured data using transfer learning, if desired.

Create your own model

Collect data in AutoML and use standard TensorFlow workflows to create your own model, then output it in binary format for deployment on the Edge TPU.

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Examples

Example application demonstrating real-time image classification for images of "dogs", "cats", or "bears".

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Specifications

Module unit

Type1WV is sold by Google.

Dimensions 15.0 × 10.0 × 1.5 mm
Chipset Google Edge TPU and PMIC
Mounting type SMT, 120-pin LGA
Serial interface PCIe Gen 2 or USB 2.0
Note
USB 3.0 is also available but requires special design considerations and support

Development board

Other products and form factors that enable the use of the Coral Edge TPU can be found at coral.ai.

CPU NXP i.MX 8M SoC (quad Cortex-A53, Cortex-M4F)
GPU Integrated GC7000 Lite Graphics
ML accelerator Google Edge TPU coprocessor: 4 TOPS (int8); 2 TOPS per watt
RAM 1 GB LPDDR4 (option for 2 GB or 4 GB coming soon)
Flash memory 8 GB eMMC, MicroSD slot
Wireless Wi-Fi 2×2 MIMO (802.11b/g/n/ac 2.4/5GHz) and Bluetooth 4.2
USB Type-C OTG; Type-C power; Type-A 3.0 host; Micro-B serial console
LAN Gigabit Ethernet port
Audio 3.5mm audio jack (CTIA compliant); Digital PDM microphone (×2); 2.54mm 4-pin terminal for stereo speakers
Video HDMI 2.0a (full size); 39-pin FFC connector for MIPI-DSI display (4-lane); 24-pin FFC connector for MIPI-CSI2 camera (4-lane)
GPIO 3.3V power rail; 40 - 255 ohms programmable impedance; ~82 mA max current
Power 5V DC (USB Type-C)
Dimensions 88 mm × 60 mm × 24mm

Technical support

For technical support, please visit Coral Support Open in New Window
For sales inquiries, please contact ASUS IoT Open in New Window

Demo video

Watch below for Type1WV demo video.