"Sipeed MAix BiT", RISC-V AI+IoT Development Board
This is where are our product comes in, MAix is Sipeed’s purpose-built module designed to run AI in these conditions. We called it AIoT, it delivers high performance in a small footprint and has a low-power consumption. This enables the deployment of high-accuracy AI and the competitive pricing makes it possible to embed any IoT devices.
As you see, Sipeed MAIX is quite like Google edge TPU, but it act as master controller, not an accelerator like Google edge TPU, so it is less costly and uses lower power than AP+edge TPU solution.
MAix's Advantage and Usage Scenarios:
- MAIX is not only hardware, but also provides 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.
- It is twice as big as the M1, 1x2 inch size, breadboard-friendly, and also SMT-capable
- It integrates USB2UART chip, auto download circuit, RGB LED, DVP Camera FPC connector(support small FPC camera and standard M12 camera), MCU LCD FPC connector (supports 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!
|CPU : RISC-V Dual Core 64bit, 400MHz adjustable||Powerful dual-core 64-bit open architecture-based processor with rich community resources|
|Debugging Support||High-speed UART and JTAG interface for debugging|
|GPIO interface||All GPIOs connected to header 2*20 2.54mm|
|Micro SD card（TF card） slot||Support Self-elastic card holder|
|One-click Download circuit||Just connect the USB typeC cable to complete the download
Onborad CH340, which support 2Mbps baudrate
|DVP Camera connector||24P 0.5mm FPC connector|
|LCD connector||8bit MCU LCD 24P 0.5mm FPC connector|
|Button||RST button and USR button|
- In hardware, MAIX has powerful KPU K210 inside, it offers many exciting 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.
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.
MAIX support original standalone SDK, FreeRTOS SDK base on C/C++.
And we ported micropython on it: https://maixpy.sipeed.com/en/ It support FPIOA, GPIO, TIMER, PWM, Flash, OV2640, LCD, etc. And it has zmodem, vi, SPIFFS on it, you can edit python directly or sz/rz file to board. We are glad to see you contribute to 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!
|FreeRTOS & Standard SDK||Support FreeRtos and Standrad development kit.|
|MicroPython Support||Support MicroPython on M1|
|Machine vision||Machine vision based on convolutional neural network|
|Machine hearing||High performance microphone array processor|
|Supply voltage of external power supply||4.8V ~ 5.2V|
|Supply current of external power supply||>600mA|
|Range of working temperature||-30℃ ~ 85℃|
- MaixPy Introduction
- Getting Started
- MAIX Bit_1.09(Assembly drawing).pdf