MAX78000 – Ultra-low-power Arm Cortex-M4 processor with FPU-based microcontroller with Convolutional Neural Network Accelerator.

The MAX78000 is is an advanced system-on-chip built to enable neural networks to execute at ultra-low power and live at the edge of the IoT. This product combines the most energy-efficient AI processing with Maxim’s proven ultra-low power microcontrollers. The hardware-based convolutional neural network (CNN) accelerator enables battery-powered applications to execute AI inferences while spending only microjoules of energy.

In addition to the memory in the CNN engine, the MAX78000 has large on-chip system memory for the microcontroller core, with 512KB flash and up to 128KB SRAM. Multiple high-speed and low-power communications interfaces are supported, including I2S and a parallel camera interface (PCIF).

The device is available in 81-pin CTBGA (8mm x 8mm, 0.8mm pitch) and 130-pin WLP (4.6mm x 3.7mm, 0.35mm pitch) packages.

Key Features

Dual Core Ultra-Low-Power Microcontroller

  • Arm Cortex-M4 Processor with FPU Up to 100MHz
  • 512KB Flash and 128KB 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 52 General-Purpose I/O Pins
  • 12-Bit Parallel Camera Interface
  • One I2S Master/Slave for Digital Audio Interface

Neural Network Accelerator

  • Highly Optimized for Deep Convolutional Neural Networks
  • 442k 8bit Weight Capacity with 1,2,4,8-bit Weights
  • Programmable Input Image Size up to 1024 x 1024 pixels
  • Programmable Network Depth up to 64 Layers
  • Programmable per Layer Network Channel Widths up to 1024 Channels
  • 1 and 2 Dimensional Convolution Processing
  • Streaming Mode
  • Flexibility to Support Other Network Types, Including MLP and Recurrent Neural Networks


About The Author

Muhammad Bilal

I am a highly skilled and motivated individual with a Master's degree in Computer Science. I have extensive experience in technical writing and a deep understanding of SEO practices.

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