Coral M.2 Accelerator with Dual Edge TPU | E-Key 2230 Module | 8 TOPS AI Coprocessor
Description
The (SPIDER Automation) Coral M.2 Accelerator with Dual Edge TPU is an advanced M.2 module (E-key) equipped with two dedicated Google Edge TPU machine learning coprocessors. Each Edge TPU is a custom ASIC that accelerates TensorFlow Lite models efficiently, performing 4 trillion operations per second (4 TOPS) using only 2 watts of power. Combined, the dual-core module delivers up to 8 TOPS of localized AI processing power.
By housing two independent Edge TPUs on a single 2230 form-factor card, this module lets you scale up edge inferencing performance—either by executing two separate vision or audio models in parallel or by pipelining a single model across both chips.
Key Features
- Dual Edge TPU ASICs: Powered by two independent Google coprocessors delivering a combined 8 TOPS (int8) performance.
- High Energy Efficiency: Delivers 2 TOPS per watt, running state-of-the-art vision models like MobileNet v2 at high frame rates.
- Parallel & Pipelined Processing: Execute multiple models simultaneously or split single deep-learning models across both processors.
- Standard M.2-2230 E-Key Layout: Compact physical dimensions (22mm × 30mm) designed for compatible system expansion slots.
- OS Integration: Built to operate smoothly on Debian-based Linux environments and Windows operating systems.
- TensorFlow Lite Ecosystem: Compiles existing TFLite models directly for hardware acceleration without rebuilding from scratch.
Benefits
- Doubled Inference Bandwidth: Double your processing capacity to 8 TOPS on a single M.2 expansion slot.
- Zero Cloud Latency: Perform real-time machine learning locally on your device for instant decision-making.
- Enhanced Data Privacy: Keep sensitive video and telemetry streams entirely secure on local hardware.
- Advanced Model Pipelining: Distribute heavy neural network layers across dual chips to optimize processing speed.
- Power-Efficient Edge AI: Scale up computational output without excessive power draw or thermal strain.
- Seamless Integration: Fits neatly into industrial mini-PCs and custom embedded gateways with dual-lane E-key slots.
Applications
- Multi-Camera Industrial Vision: Running parallel object detection and sorting streams on automated factory lines.
- Advanced Surveillance Gateways: Simultaneous facial recognition, anomaly detection, and vehicle tracking.
- Robotics & Autonomous Navigation: Processing complex spatial awareness models and environmental mapping locally.
- Smart Retail Analytics: Multi-angle customer traffic monitoring and behavior analysis without cloud overhead.
- Edge AI Prototyping: Developing high-performance neural network pipelines on embedded Linux development boards.
- Medical & Scientific Imaging: Local pattern recognition and rapid automated diagnostics in compact hardware enclosures.
Package Includes
- 1 x Coral M.2 Accelerator with Dual Edge TPU
Technical Specifications
| Parameter | Specification |
|---|---|
| Item Type | Dual-Core AI Accelerator Module |
| Brand | SPIDER Automation |
| Model Series | Coral |
| Processor / Coprocessor | Dual Google Edge TPU ML Accelerators (ASIC) |
| Total AI Performance | 8 TOPS Combined (4 TOPS per Edge TPU at 2W / 2 TOPS per Watt) |
| Hardware Interface | M.2 E-Key (Requires dual PCIe Gen2 x1 lanes) |
| Supported Framework | TensorFlow Lite (TFLite) via PyCoral, Libcoral, and Libedgetpu APIs |
| Supported Operating Systems | Debian-based Linux & Windows 10/11 systems |
| Product Dimensions (L × W × H) | 22 mm × 30 mm × 2.8 mm (M.2-2230 Form Factor) |
| Gross Shipping Weight | 0.015 kg |
| Package Shipping Dimensions | 6 cm × 5 cm × 2 cm |
