M1W AI+lOT Module K210 Deep learning

Note: M1W AI+lOT Module K210 Deep learning is discontinued now.

AI chip normally refers to an ASIC chip that aims at AI algorithms. Although the conventional CPU and GPU can be used to execute AI algorithms, they have been greatly limited in their speed, performance, and practicality. Compared with traditional processor chips, AI chip offers faster speed, more computing power, and low energy consumption.

This product employs AI chip K210 as the core unit. K210 comes with dual-core processors with independent FPU, 64 bits CPU bit width, 8MB on-chip SRAM, 400M adjustable nominal frequency, and double-precision FPU supporting multiplication, division, and square root operation.

The AI Module-M1 is equipped with a neural network hardware accelerator KPU, voice processing unit (APU), programmable IO array (FPIOA/IOMUX), and Fast Fourier Transform Accelerator. In AI processing, K210 can perform operations such as convolution, batch normalization, activation, and pooling. At the same time, the pre-processing of voice direction scanning and voice data output can also be performed.

M1W module has a WIFI function based on M1chip.

• CPU: RISC-V dual-core 64 bit 

                  400Mhz standard frequency (overclockable)

• Debugging Support: high-speed UART and JTAG interface for debugging
• Neural Network Processor: each payer of convolutional neural network parameter can be configured separately, including the number of inpu and output channels, and the input and output line width and column height.

                                                         Support for 1×1 and 3×3 convolution kernels

• Image Recognition: QVGA@60FPS/VGA@30FPS
• Audio Processor: support up to 8 channels of audio input data, ie 4 stereo channels

                                       16 bit wide internal audio signal processing                                 

                                       Support for 12 bit, 16 bit, 24 bit and 32-bit input data widths                                  

                                       Up to 192KHz sample rate

• Static Random-Access Memory(SRAM): the SRAM is split into two parts, 6MiB of on-chip general-purpose SRAM and 2 MiB of on-chip AI SRAM
• Field-Programmable IO Array: FPIOA allows users to map 255 internal functions to 48 free IOs on the chip
• Digital Video Port: maximum frame size 640 x 480 
• FFT Accelerator: the FFT accelerator is a hardware implementation of the Fast Fourier Transform(FFT)
• Deep Learning: TensorFlow/Keras/Darknet
• Peripherals: FPIOA, UART, GPIO, SPI, I2C, I2S, WDT, TIMER, RTC, etc.
• WiFi: support 2.4G 802.11.b/g/n

• Dimension: 25.4  25.4 3.3mm/110.13”
• 72-pin Full Lead-out
• Input Voltage: 5.0V±0.2V(DC)
• Input Current: >300mA(5V)
• Operating Temperature: -30ºC~85ºC
• Compliant with IEEE754-2008 Standard
• MCU: ESP8285 Tensilica L106 32-bit MCU
• Wireless Standard: 802.11b/g/n
• Frequency Range: 2400Mhz-2483.5Mhz
• Transmit Power(Conduction Test): 802.11.b:+15dBm

                                                                      802.11.g:+10dBm(54Mbps)                                                             

                                                                      802.11.n:+10dBm(65Mbps)

• WiFi Mode: Station/SoftAP/SoftAP+Station
• Communication Interface: serial port

AI Module-M1W x1