AAEON LAUNCHES M.2 AND MINI-PCIE BASED AI ACCELERATORS USING LOW-POWER KNERON NPU

Aaeon’s M.2 and mini-PCIe “AI Edge Computing Modules” are based on Kneron’s energy-efficient, dual Cortex-M4-enabled KL520 AI SoC, which offers 0.3 TOP NPU performance on only half a Watt. by Eric Brown @ linuxgizmos.com

Aaeon took an early interest in edge AI acceleration with Arm-based Nvidia Jetson TX2 based computers such as the Boxer-8170AI. More recently, it has been delivering M.2 and mini-PCIe form-factor AI Core accessories for its Boxer computers and UP boards equipped with Intel Movidius Myriad 2 and Myriad X Vision Processing Units (VPUs). Now, it has added another approach to AI acceleration by launching a line of M.2 and mini-PCIe AI acceleration cards built around Kneron’s new KL520 AI SoC.

Aaeon is taking orders for three KL520-based AI Edge Computing Modules cards aimed at IoT, smart home, security, and mobile devices:

  • M2AI-2280-520 — M.2 B-Key 2280
  • M2AI-2242-520 — M.2 2242
  • Mini-AI-520 — mini-PCIe

Aaeon’s 0 to 70°C tolerant AI Edge Computing Modules operate at 0.5W to 0.9W. There do not appear to be any functional differences between the three modules, which all supply UART and JTAG debug interfaces and communicate with the host processor via USB signals. The modules support acceleration for ONNX, TensorFlow, Keras, Caffe frameworks with models including Vgg16, Resnet, GoogleNet, YOLO, Tiny YOLO, Lenet, MobileNet, and DenseNet.

The KL520 AI SoC combines dual Cortex-M4 MCUs with Kneron’s Neural Processing Unit (NPU) chip, which can be licensed separately. The power-efficient KL520 supports co-processor use, as deployed in Aaeon’s AI Edge Computing Modules, in scenarios that would typically connect to an embedded Linux computer. The SoC can also be used as a standalone, AI-enabled IoT node in applications such as smart door locks.

The KL520 AI SoC is designed to accelerate general AI models such as facial and object recognition, gesture detection, and driver behavior for AIoT applications including access control, automation, security, and surveillance. It can also be used to monitor consumer behavior in retail settings – a trend that could push even more customers to shop online. Aaeon notes, however, that the solution enhances privacy — and reduces latency — because edge AI devices do not require a cloud connection.

Read more: AAEON LAUNCHES M.2 AND MINI-PCIE BASED AI ACCELERATORS USING LOW-POWER KNERON NPU

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