The RK1808 chip by Rockchip is a powerful yet energy-efficient solution tailored for edge AI inference applications. Equipped with dual-core ARM Cortex-A35 CPUs and a dedicated Neural Network Processor (NPU), it offers exceptional performance in machine learning and deep learning tasks. With its low power consumption and high processing efficiency, the RK1808 is ideal for mobile devices, smart cameras, voice recognition systems, and AIoT applications.
This processor supports ARM Neon for SIMD acceleration and VFPv4 for enhanced floating-point calculations. The architecture includes L1 and L2 caches, which ensure quick data access and stable performance under high workloads.
The RK1808 is fully compatible with popular deep learning frameworks, including TensorFlow, Caffe, and others. It is designed to be integrated easily into edge devices, enabling real-time AI processing and inference without relying on cloud computing.
📐 Technical Specifications
| Parameter | Details |
|---|---|
| CPU | Dual-core ARM Cortex-A35 |
| SIMD Support | ARM Neon (Advanced SIMD) |
| Floating Point Unit | VFPv4 – single and double precision |
| Cache | 32KB L1 I-Cache, 32KB L1 D-Cache (4-way), 128KB unified L2 |
| NPU | Integrated Neural Network Processor for AI inference |
| AI Frameworks | TensorFlow, Caffe, MXNet, and more |
| Power Domains | Separate PD_CPU0 and PD_CPU1 for optimized power management |
| Process Technology | Low-power design with DVFS (Dynamic Voltage and Frequency Scaling) |
| Package Type | BGA / QFN (depends on configuration) |
| Operating Voltage | Configurable by domain, power-efficient |
🎯 Applications
-
AIoT Devices: Smart home appliances, wearables, and embedded AI devices
-
Edge AI Devices: Smart cameras, voice recognition modules, and security systems
-
Industrial AI: Real-time data processing and edge computing
-
Mobile Devices: High-performance AI tasks for mobile terminals
-
Automotive: AI-powered in-car devices for vision and voice processing
Reviews
There are no reviews yet.