Sipeed MAIX Bit RV64 인공지능 플랫폼 모듈 + LCD 키트

(Sipeed MAix BiT Kit for RISC-V AI+IoT)

개요

  • 본 제품은 edge computing을 위한 Sipeed MAIX Bit RV64 인공지능 플랫폼 보드와 LCD 디스플레이가 포함되 제품입니다.
  • Sipeed사의 MAIX 시리즈 보드중 제일 작은 보드로, APU (8X mics (up to 192KHz sample rate)지원), 보드의 48개 GPIO를 매핑할 수 있는 FPIOA (Field Programmable I/O Array)를 지원합니다.
  • microSD 슬롯(8Mb SPI Flash), MCU LED FPC 디스플레이 커넥터, DVP FPC 카메라 커넥터, 1 USB Type C 포트를 지원합니다.
  • USB 포트를 통해 전원을 공급하고 프로그래밍을 할 수 있습니다.
  • 같이 사용할 수 있는 LCD 디스플레이가 포함되어 있습니다.

특징

  • MAix's Advantage and Usage Scenarios:

    • MAIX is not only hardware, but also provide an end-to-end, hardware + software infrastructure for facilitating the deployment of customers' AI-based solutions.
    • Thanks to its performance, small footprint, low power, and low cost, MAIX enables the broad deployment of high-quality AI at the edge.
    • MAIX isn't just a hardware solution, it combines custom hardware, open software, and state-of-the-art AI algorithms to provide high-quality, easy to deploy AI solutions for the edge.
    • MAIX can be used for a growing number of industrial use-cases such as predictive maintenance, anomaly detection, machine vision, robotics, voice recognition, and many more. It can be used in manufacturing, on-premise, healthcare, retail, smart spaces, transportation, etc.

    MAix's CPU

    • In hardware, MAIX have powerful KPU K210 inside, it offers many excited features:
    • 1st competitive RISC-V chip, also 1st competitive AI chip, newly release in Sep. 2018
    • 28nm process, dual-core RISC-V 64bit IMAFDC, on-chip huge 8MB high-speed SRAM (not for XMR :D), 400MHz frequency (able to 800MHz)
    • KPU (Neural Network Processor) inside, 64 KPU which is 576bit width, support convolution kernels, any form of activation function. It offers 0.25TOPS@0.3W,400MHz, when overclock to 800MHz, it offers 0.5TOPS. It means you can do object recognition 60fps@VGA
    • APU (Audio Processor) inside, support 8mics, up to 192KHz sample rate, hardcore FFT unit inside, easy to make a Mic Array (MAIX offer it too)
    • Flexible FPIOA (Field Programmable IO Array), you can map 255 functions to all 48 GPIOs on the chip
    • DVP camera and MCU LCD interface, you can connect an DVP camera, run your algorithm, and display on LCD
    • Many other accelerators and peripherals: AES Accelerator, SHA256 Accelerator, FFT Accelerator (not APU's one), OTP, UART, WDT, IIC, SPI, I2S, TIMER, RTC, PWM, etc.

    MAix's Module

    Inherit the advantage of K210's small footprint, Sipeed MAIX-I module, or called M1, integrate K210, 3-channel DC-DC power, 8MB/16MB/128MB Flash (M1w module add wifi chip esp8285 on it) into Square Inch Module. All usable IO breaks out as 1.27mm(50mil) pins, and pin's voltage is selectable from 3.3V and 1.8V.

    Sipeed Maix  block pin

    Sipeed MAix BiT development board

    As many DIYer want build their own work with breadboard, Sipeed newly provide breadboard-friendly board for you, it called MAix BiT

    • It is twice of M1 size, 1x2 inch size, breadboard-friendly, and also SMT-able,
    • It integrate USB2UART chip, auto download circuit, RGB LED, DVP Camera FPC connector(support small FPC camera and standard M12 camera), MCU LCD FPC connector(support our 2.4 inch QVGA LCD), TF card solt.
    • MAix BiT is able to adjust core voltage! you can adjust from 0.8V~1.2V, overclock to 800MHz!
    2 bit

    MAix's SoftWare

    MAIX support original standalone SDK, FreeRTOS SDK base on C/C++.
    And we port micropython on it: http://en.maixpy.sipeed.com/. It support FPIOA, GPIO, TIMER, PWM, Flash, OV2640, LCD, etc. And it have zmodem, vi, SPIFFS on it, you can edit python directly or sz/rz file to board. We are glad to see you contribute for it:
    https://github.com/sipeed/MaixPy //Maixpy project
    https://github.com/sipeed/MaixPy_Doc_Us_En_Backup //Maixpy wiki project

    MAix's Deep learning

    MAIX support fixed-point model that the mainstream training framework trains, according to specific restriction rules, and have model compiler to compile models to its own model format.
    It support tiny-yolo, mobilenet-v1, and, TensorFlow Lite! Many TensorFlow Lite model can be compiled and run on MAIX! And We will soon release model shop, you can trade your model on it.

문서

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