Artificial intelligence (AI) requires extreme computational horsepower, but Analog Devices is cutting the power cord from AI insights. The MAX78002 is a new breed of AI microcontroller that enables neural networks to execute at ultra-low power and live at the edge of the IoT. This device combines the most energy-efficient AI processing with Analog Devices' proven ultra-low-power microcontrollers. Our hardware-based CNN accelerator enables battery-powered applications to execute AI inferences while expending only millijoules of energy.
The MAX78002 is an advanced system-on-chip featuring an Arm® Cortex®-M4 with FPU CPU for efficient system control with an ultra-low-power deep neural-network accelerator. The CNN engine has a weight storage memory of 2MB, and can support 1-, 2-, 4-, and 8-bit weights (supporting networks of up to 16 million weights). The CNN weight memory is SRAM-based so that AI network updates can be made on the fly. The CNN engine also has 1.3MB of data memory. The CNN architecture is highly flexible, allowing networks to be trained in conventional toolsets like PyTorch® and TensorFlow®, then converted for execution on the MAX78002 using tools provided by Analog Devices.
In addition to the memory in the CNN engine, the MAX78002 has large on-chip system memory for the microcontroller core with 2.5MB flash and up to 384KB SRAM. Multiple high-speed and low-power communications interfaces are supported, including I2S, MIPI® CSI-2® serial camera, parallel camera (PCIF), and SD 3.0/SDIO 3.0/eMMC 4.51 secure digital.
The device is available in a 144 CSBGA, 12mm x 12mm, 0.8mm pitch package.