Analog Devices MAX78002 Artificial Intelligence Microcontrollers are AI microcontrollers that enable neural networks. The Analog Devices MAX78002 can execute at ultra-low power and live at the edge of the IoT. The devices combine energy-efficient AI processing with ultra-low-power microcontrollers. This hardware-based CNN accelerator enables battery-powered applications to execute AI inferences while expending only millijoules of energy.
Features
Dual-core, low-power microcontroller
Arm® Cortex®-M4 processor with FPU up to 120MHz
2.5MB Flash, 64KB ROM, and 384KB SRAM
Optimized performance with 16KB instruction cache
Optional error correction code (ECC SEC-DED) for SRAM
32-bit RISC-V coprocessor up to 60MHz
Up to 60 general-purpose I/O pins
MIPI camera serial interface 2 (MIPI CSI-2) controller V2.1 - support for two data lanes
12-bit parallel camera interface
I2S controller/target for digital audio interface
Secure Digital interface supports SD 3.0/SDIO 3.0/eMMC 4.51
Convolutional Neural Network (CNN) accelerator
Highly optimized for deep CNNs
2 million 8-bit weight capacity with 1-, 2-, 4-, and 8-bit weights
1.3MB CNN data memory
Programmable input image size up to 2048x2048 pixels
Programmable network depth of up to 128 layers
Programmable per layer network channel widths up to 1024 channels
1- and 2-dimensional convolution processing
Capable of processing VGA images at 30fps
Power management for extending battery life
Integrated Single-Inductor Multiple-Output (SIMO) Switch-Mode Power Supply (SMPS)
2.85V to 3.6V supply voltage range
Support of optional external auxiliary CNN power supply
Dynamic voltage scaling minimizes active core power consumption
23.9μA/MHz while loop execution at 3.3V from cache (CM4 only)
Selectable SRAM retention in low-power modes with Real-Time Clock (RTC) enabled
Security and integrity
Available secure boot
AES 128/192/256 hardware acceleration engine
True Random Number Generator (TRNG) seed generator
