Development Boards & Kits G950-06210-01

ARM This new Dev Board version has the same build as the existing 1 GB Dev Board with 4 GB RAM built in.
Coral Dev Board is a single-board computer with a removable system-on-module (SOM) that contains eMMC, SOC, wireless radios, and Google’s Edge TPU. It’s perfect for IoT devices and other embedded systems that demand fast on-device ML inferencing. The Dev Board can be used as a single-board computer for accelerated ML processing in a small form factor, or as an evaluation kit for the on-board SOM. Additional 40mm × 48mm SOMs can be combined with your custom PCB hardware using board-to-board connectors for integration into products. 1GB and 4GB LPDDR4 versions available.

The SOM is based on NXP’s iMX8M system-on-chip (SOC), but its unique power comes from the Edge TPU coprocessor. The Edge TPU is a small ASIC designed by Google that provides high performance ML inferencing with a low power cost. For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at 100+ fps in a power efficient manner.

Edge TPU key benefits:
– High speed TensorFlow Lite inferencing
– Low power
– Small footprint

Coral, a division of Google, helps build intelligent ideas with a platform for local AI.

Category:

SPECIFICATIONS
SOM
NXP i.MX 8M SoC (Quad-core Cortex-A53, plus Cortex-M4F)
Google Edge TPU ML Accelerator Coprocessor
Cryptographic coprocessor
Wi-Fi 2×2 MIMO (802.11b/g/n/ac 2.4/5GHz)
Bluetooth 4.1
8GB eMMC
1GB and 4GB LPDDR4 versions
USB Connections
USB Type-C power port (5V DC)
USB 3.0 Type-C OTG port
USB 3.0 Type-A host port
USB 2.0 Micro-B serial console port
Audio Connections
3.5mm audio jack (CTIA compliant)
Digital PDM microphone (x2)
2.54mm 4-pin terminal for stereo speakers

Video Connections
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)
MicroSD card slot
Gigabit Ethernet port
40-pin GPIO expansion header
Supports Debian Linux
Models are built using TensorFlow
Fully supports MobileNet and Inception architectures, though custom architectures are possible
Compatible with Google Cloud

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