Edgeless EAI-Series Dual Arm Cortex-M4 MCU Features a 300 GOPS CNN-NPU

Microcontrollers will have an important role to play in AIoT (AI + IoT) applications as they provide the lowest cost and power consumption. Performance is limited but we start seeing MCUs with AI accelerators such as GreenWaves GAP9 multi-core RISC-V microcontroller or Kendryte K210 RISC-V MCU with a KPU AI accelerator.

Another option is by Edgeless Semiconductor Co. Ltd (零边界集成电路有限公司) based in Zhuhai, China, and more specifically its Edgeless EAI-Series dual-core Arm Cortex-M4 microcontrollers equipped with a 300 GOPS CNN NPU.

Edgeless EAI-Series MCU Packages
Edgeless EAI-Series MCUs are available in various packages from 40-pin QFN to 176-pin LQFP

Edgeless EAI specifications:

  • CPU – Dual Arm Cortex-M4F @ up to 200Mhz, with DSP instructions, I/D cache for high performance; 500DMIPS/1.25DMIPS/MHz (Dhrystone2.1)
  • AI Accelerator – CNN-NPU clocked at up to 300MHz with 300 GOPS peak throughput; 144MAC/cycle, EER up to 1TOPS/W, for image recognition scenario.
    • Support major CNN Models including Resnet-18,
      Resnet-34, Vgg16, GoogleNet, Lenet, etc..
    • Support Convolutional kernel size 1~7
    • Support Channel/Feature No. up to 512
    • Support Max/Average pooling function
    • Arithmetic Precision: 16-bit fixed-point
  • Memory
    • Up to 384KB of SRAM, 256KB for CNN-NPU (Share with CPU)
    • Up to 8MB of SIP-SDRAM
    • Flexible external memory control: SRAM, PSRAM,
  • Storage – 4KB OTP for system BootROM, external SPI NOR/NAND Flash, 1x SD/MMC up to 25 MB/sec data transfer for 8-bit mode
  • CRC calculation unit
  • Clock, reset and supply management
    • 1.7~3.6V application supply and I/Os
    • POR, PDR, PVD, and LVD
    • 4 to 26 MHz crystal oscillator
    • Internal 8 MHz RC (1% accuracy)
    • PLL – PLLKDP 300MHz clock; PLL 180~216MHz clock;  PLLSAI 192MHz clock;  PLLI2S 48MHz clock
    • 30kHz internal RC for watchdog or RTC
    • 32.768kHz external crystal for RTC
  • Low power modes
    • Run, Sleep, Stop 1/2, Standby, Shutdown
    • Backup domain VBAT supply for RTC
  • 12-bit 2.4MSPS SAR-ADC with 16 channel
  • One analog comparator module (ACMP) with
    12-bit 4096-level DAC
  • Dedicated 2D Graph Accelerator
    • IMP supporting image copy, format convert,
      blending, scaling and Harris corner detection
    • VIN, 8- to 14-bit parallel camera interfaces, DVP
      mode, up to 54 Mbytes/s
    • VOUT supporting multi-format TFT-LCD video
      output up to 1024×768 resolution
  • One low gate count 16-ch DMA for M2M, P2M,
    M2P, P2P data transaction with FIFO and burst
  • Security modules
    • CRYPTO, data en/decryption algorithm, AES/3DES/DES and HASH/HMAC
    • TRNG, true random number generator
    • OTP, secure data and BootROM code
  • Up to 18 timers
    • Up to 4x 16-bit and 2x 32-bit timers up to 200 MHz, each with up to 4 IC/OC or pulse counter and the generation of PWM signals
    • 1x RTC (Battery back-up domain)
    • 1x WWDG (Window watchdog timer)
    • 1x IWDG (Independent watchdog timer)
    • 1x SysTick timer
  • Other Peripherals
    • Up to 3x I2C interfaces
    • Up to 8x UARTs with full-duplex data exchange,
    • Up to 2x SPIs, full-duplex synchronous and single-wire bidirectional mode and 4- to 16-bit word frames
    • Up to 1x CAN 2.0B interfaces
    • 1x USB 2.0 full-speed device/host/OTG controller with off-chip PHY
    • 2x SAI (Serial Audio Interface) and 4x PDM
    • Up to 161x I/O ports with interrupt capability
  • Debugging – Serial wire debug (SWD),  Cortex-M4 Trace Macrocell
  • Packages (QFN, LQFP):
    • EAI60 – QFN40 with 2MB SDRAM
    • EAI68 – QFN40 with 8MB SDRAM
    • EAI80 – QFN80 with 8MB SDRAM
    • EAI88 – LQFP128
    • EAI90 – LQFP144
    • EAI98 – LQFP176

The company does not appear to have a website, but I found the datasheet via a Banana Pi private group on Facebook as Banana Pi is currently designing an EAI80 development board.

Edgeless EAI80 Development Board

The board also includes an ESP8266 WiFI module, a 40-pin GPIO interface, connectors for LCD and cameras, two microphones, a USB-C port, a CAN bus header, and a battery header. This reminds me of Maixduino SBC, but except of being RISC-V-based, it is Arm-based and features an ESP8266 module instead of one with ESP32. Both connect to a camera & a display, and perform AI inference (computer vision/audio processing) on low-end hardware.

That’s all the information I have for now, and no details about the SDK has been leaked so far. It will likely take a little longer before such SoC and board become available.

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