Allwinner V853 Arm Cortex-A7 + RISC-V SoC comes with 1 TOPS NPU for AI Vision applications

Allwinner V853 SoC combines an Arm Cortex-A7 core with a Xuantie E907 RISC-V core, and a 1 TOPS NPU for cost-sensitive AI Vision applications such as smart door locks, smart access control, AI webcams, tachographs, and smart desk lamps.

Manufactured with a 22nm process, the SoC comes with an ISP image processor and Allwinner Smart video engine capable of up to 5M @ 30fps H.265/H.264 encoding and 5M @ 25fps H.264 decoding, offers parallel CSI and MIPI CSI camera interfaces, and well as MIPI DSI and RGB display interfaces.

Allwinner V853 specifications:

  • CPU
    • Arm Cortex-A7 CPU core @ 1 GHz with 32 KB I-cache, 32 KB D-cache, and 128 KB L2 cache
    • Alibaba Xuantie E907 RISC-V core with 16 KB I-cache and 16 KB D-cache
  • NPU (Neural network Processing Unit) – Up to 1 TOPS for V853 and 0.8 TOPS for V853S,  embedded 128KB internal buffer, support for TensorFlow, Caffe, Tflite, Pytorch, ONNX, etc..
  • VPU (Video Processing Unit)
    • Encoding
      • H.265/H.264 encoding up to 3840×2160 @ 20fps
      • Multi-stream real-time encoding up to 5M @ 25fps + 720p @ 25fps
      • MJPEG/JPEG baseline encoding up to 1080p60
    • Decoding – H.264/JPEG decoding up to 16 megapixels (4096×4096)
  • Memory I/F – 16-bit DDR3/DDR3L
  • Storage I/F – SD 3.0/eMMC 5.1 flash, SPI NOR/SPI NAND flash
  • Video Output
    • 4-lane MIPI DSI up to 1920 x 1200 @ 60fps
    • RGB interface with DE/SYNC mode up to 1920 x 1080 @ 60fps
  • Video Input
    • ISP supporting up to 5M @ 30 fps, and a maximum resolution of 3072 x 3072
    • Parallel CSI supporting 8/10/12/16-bit width
    • 4-lane MIPI CSI input or two 2-lane MIPI CSI inputs; maximum video capture resolution up to 5M @ 30fps
  • Audio
    • 1x 16-bit/20-bit DAC with 8 kHz to 192 kHz sample rate
    • 2x 16-bit/20-bit ADC with 8 kHz to 48 kHz sample rate
    • 2x differential microphone inputs: MICIN1P/N, MICIN2P/N
    • 1x differential lineout output (LINEOUTP/LINEOUTN)
    • 2x I2S/PCM external interfaces (I2S0, I2S1)
    • Up to 8 digital PDM microphones with sample rates from 8 kHz to 48 kHz
  • Other Peripherals
    • 5x TWI (I2C) interfaces, 4x UART interfaces, 4x SPI interfaces
    • 8x GPIO, 1x 12-ch PWM controller
    • 4x general-purpose analog-to-digital converter (GPADC)
    • USB 2.0 DRD
  • Package – LFBGA 318
  • Process – 22nm
Typical Allwinner V853/R853S application block diagram

A thread on a Chinese forum mentions the NPU on V853 is “very open” not like the one on V831, and Allwinner also provides a V851 model with 64MB or 128MB built-in memory. The Allwinner R853 is the same but designed for robots with motor control. I suppose R853S shown above is a variant with a 0.8 TOPS NPU like for V853S… More details specifications can be found on linux-sunxi website. The Arm Cortex-A7 should probably run Linux (OpenWrt based TinaLinux?), and the RISC-V MCU core handles low power modes and I/Os, but it is not entirely clear how they work together, and which core handles what.

MangoPi team is also working on a compact (27.5×42.5 mm) MQ-V Ai Core module based on Allwinner V853 with 512 MB DDR3, 8GB eMMC flash, and an AXP2101 PMU, so we’ll certainly find out more in a couple of months.

Share this:

Support CNX Software! Donate via PayPal or cryptocurrencies, become a Patron on Patreon, or buy review samples

7 Replies to “Allwinner V853 Arm Cortex-A7 + RISC-V SoC comes with 1 TOPS NPU for AI Vision applications”

  1. Any links to the SDK so we can see whether it’s a similar NPU to the V831 which I mainly reversed engineered?

    1. The npu of 853 is VeriSilicon ip, which is very similar to rk356x. This is completely different from the 833.

  2. Since this has binocular cameras, I wonder if it can do hardware depth mapping without utilizing all of the NPU. Maybe ISP can do it?

    This chip appears to have all of the peripherals I need, but what is the price?

    Do these disparate CPUs both run out of the same DRAM? How do you communicate between them, can they safely place locks in memory?

Leave a Reply

Your email address will not be published.

Advertisement
Advertisement