Analog Devices' AI MCU features a low-power convolution Neural network (CNN) accelerator

     Analog Devices' MAX78002 is an AI MCU that enables neural networks to execute at ultra-low power, at the edge of the Internet of Things. The device comes in a 144 CSBGA, 12 mm x 12 mm, 0.8mm pitch package. And combines the most energy-efficient AI processing with Analog Devices' proven ultra-low power MCU. Hardware-based CNN accelerators enable battery-powered applications to perform AI reasoning while consuming only millifocal energy.

     The MAX78002 is an advanced system-on-chip, Arm Cortex-M4 with an FPU CPU, featuring an ultra-low power deep neural network accelerator for efficient system control. The CNN engine has 2 MB of weight storage and can support 1 -, 2 -, 4 -, and 8-bit weights (up to 16 million weight networks). CNN weight memory is based on SRAM and therefore allows real-time AI network updates.

     The CNN engine also has 1.3 MB of data memory. The CNN architecture is highly flexible, allowing the network to be trained using conventional toolsets such as PyTorch and TensorFlow and then converted to execute on the MAX78002 using tools provided by Analog Devices.

     In addition to the memory for the CNN engine, the MAX78002 has large system-on-chip memory for the microcontroller kernel, with 2.5 MB flash memory and a maximum 384 KB SRAM. Supports a variety of high-speed and low-power communication interfaces, including I2S, MIPI® CSI-2® serial cameras, parallel cameras (PCIF), and SD 3.0/SDIO 3.0/eMMC 4.51 SD cards.