VEGA-230 ADVANTECH | Alldatasheet
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Technical content
Features
Kneron KL520 NPU onboard Mini PCI-E card (USB2.0 interface, full size) Accelerator for Edge AI solution Maximize power efficiency and performance Supports wide AI frameworks and CNN* models Introduction Advantech has collaborated with Kneron to deliver modules featuring their innovative AI edge computing processor. The KL520 NPU (Neural Processor Unit) with its dual ARM Cortex M4 CPU can operate as a host or companion AI co-processor enabling edge AI on devices like smart locks, security cameras, drones, smart home appliances, and robotics. It is compatible with various 3D sensor technologies such as Structured Light, dual-cameras, ToF camera, and Kneron’s own exclusive 3D sensing technology. Advantech VEGA-230 is compatible with all of EI/EIS/AIR solutions platform which support mPCIe modules. The VEGA-230 offers the best in performance, efficiency, and cost effectiveness. Specifications VEGA-230-01A1 SoC Kneron KL520 Form Factor Full size Mini PCIe Dimensions 30 x 50.95 x 4.80 mm Signal Interface USB 2.0 Operating Temp. 0°C ~ 70°C Power Consumption 0.5W Cooling Passive Cooling NPU Performance 0.35 TOPS AI Framework Support ONNX, TensorFlow, Keras, Caffe, PyTorch CNN Model Support ResNet, GoogleNet, VGG16, LeNet, MobileNet, DenseNet, YOLO, Tiny YOLO, and more Kneron KL520 Edge AI Module NEW *Convolutional Neural Network (CNN) All product specifications are subject to change without notice. Last updated: 17-Mar-2021
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Ordering Information
VEGA-230-01A1 Full size miniPCIe Edge AI acceleration module with Kneron KL520 Packing List Part Number Description VEGA-230-01A1 1 x VEGA-230 Module 1 x M3 screw Dimensions Block Diagram Unit: mm Reconfigurable Solutions Most AI models are limited to specific applications and frameworks. Kneron's Reconfigurable Artificial Neural Network (RANN) technology adapts in real-time to audio, 2D, or 3D recognition applications while also being compatible with mainstream AI frameworks and convolutional neural network (CNN) models. RANN Technology can: Compute audio and images including 2D/3D visual recognition Support AI frameworks: ONNX, TensorFlow, Keras, Caffe, PyTorch Support CNN models: ResNet, GoogleNet, VGG16, LeNet, MobileNet, DenseNet, YOLO, Tiny YOLO, and more RANN Technology helps partners: Lower costs by up to 20% Create commercial applications Customize edge AI to fit unique use cases 30.00 4.80 1.00 2-Ø2.60 24.20 50.95 48.05