Overview
Coral M.2 Accelerator is a Google Coral Edge TPU device sold by Seeed Studio, rated by Seeed at 8 TOPS (int8). Seeed publishes a fixed price for this configuration.
Key Features
- Coral M.2 Accelerator with Dual Edge TPU rated at 8 TOPS (int8)
- ML accelerator: 2x Google Edge TPU coprocessor:8 TOPS (int8); 2 TOPS per watt
- Hardware Interface: M.2 E-key (M.2-2230-D3-E)
- Serial Interface: Two PCIe Gen2 x1
- Performs high-speed ML inferencing: Each Edge TPU coprocessor is capable of performing 4 trillion operations per second (4 TOPS), using 2 watts of power. Fo
- Works with Debian Linux and Windows: Integrates with Debian-based Linux or Windows 10 systems with a compatible card module slot.
Ideal For
developers running quantised TensorFlow Lite models at the edge on an Edge TPU rather than a GPU
ML accelerator
2x Google Edge TPU coprocessor:8 TOPS (int8); 2 TOPS per watt
Hardware Interface
M.2 E-key (M.2-2230-D3-E)
Serial Interface
Two PCIe Gen2 x1
Operating Voltage
3.3V +/- 10%
Storage Temperature
-40 to +85°C
Operating Temperature
-40 to +85°C
Relative Humidity
0 to 90% (non-condensing)
Performs high-speed ML inferencing
Each Edge TPU coprocessor is capable of performing 4 trillion operations per second (4 TOPS), using 2 watts of power. For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at almost 400 FPS, in a power-efficient manner. With the two Edge TPUs in this module, you can double the inferences per second (8 TOPS) in several ways, such as by running two models in parallel or pipelining one model across both Edge TPUs.
Works with Debian Linux and Windows
Integrates with Debian-based Linux or Windows 10 systems with a compatible card module slot.
Supports TensorFlow Lite
No need to build models from the ground up. TensorFlow Lite models can be compiled to run on the Edge TPU.
Supports AutoML Vision Edge
Easily build and deploy fast, high-accuracy custom image classification models to your device with AutoML Vision Edge.
Prices may vary. Verify on vendor site.
Quick Specs
- ML accelerator
- 2x Google Edge TPU coprocessor:8 TOPS (int8); 2 TOPS per watt
- Hardware Interface
- M.2 E-key (M.2-2230-D3-E)
- Serial Interface
- Two PCIe Gen2 x1
- Operating Voltage
- 3.3V +/- 10%
- Storage Temperature
- -40 to +85°C
- Operating Temperature
- -40 to +85°C