MAX78002 Artificial Intelligence (AI) Microcontroller (MCU)

Product Highlights > MAX78002 Artificial Intelligence (AI) Microcontroller (MCU)

            MAX78002 Artificial Intelligence (AI) Microcontroller (MCU)
                    Analog Devices' AI MCU features a low-power convolutional neural network (CNN) accelerator
    

Analog Devices' MAX78002 is a breed of AI MCU 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 MCUs. The 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 2 MB 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 1.3 MB 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 2.5 MB Flash and up to 384 KB SRAM. Multiple high-speed and low-power communications interfaces, including I2S, MIPI® CSI-2® serial camera, parallel camera (PCIF), and SD 3.0/SDIO 3.0/eMMC 4.51 secure digital, are supported.

The device is available in a 144 CSBGA, 12 mm x 12 mm, 0.8 mm pitch package.

The MAX78002 evaluation kit (MAX78002EVKIT#) provides a platform and tools for leveraging device capabilities to build new generations of AI products.

Features

Dual-core, low-power MCU

Arm Cortex-M4 processor with FPU up to 120 MHz
2.5 MB Flash, 64 KB ROM, and 384 KB SRAM
Optimized performance with 16 KB instruction cache
Optional error correction code (ECC SEC-DED) for SRAM
32-bit RISC-V coprocessor up to 60 MHz
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
1.3 MB CNN data memory
Programmable input image size up to 2048 pixels x 2048 pixels
Programmable network depth 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 30 fps

Power management for extending battery life

Integrated single-inductor multiple-output (SIMO) switch-mode power supply (SMPS)
2.85 V to 3.6 V supply voltage range
Support of optional external auxiliary CNN power supply
Dynamic voltage scaling minimizes active core power consumption
23.9 μA/MHz while loop execution at 3.3 V from cache (CM4 only)
Selectable SRAM retention in low-power modes with real-time clock (RTC) enabled