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Atlas 200 Module Ascend Ai Board 8 Gb 128 Bits Lpddr4x 64mb Emmc 4.5 Ubuntu System

Beijing Plink AI Technology Co., Ltd
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    Buy cheap Atlas 200 Module Ascend Ai Board 8 Gb 128 Bits Lpddr4x 64mb Emmc 4.5 Ubuntu System from wholesalers
     
    Buy cheap Atlas 200 Module Ascend Ai Board 8 Gb 128 Bits Lpddr4x 64mb Emmc 4.5 Ubuntu System from wholesalers
    • Buy cheap Atlas 200 Module Ascend Ai Board 8 Gb 128 Bits Lpddr4x 64mb Emmc 4.5 Ubuntu System from wholesalers
    • Buy cheap Atlas 200 Module Ascend Ai Board 8 Gb 128 Bits Lpddr4x 64mb Emmc 4.5 Ubuntu System from wholesalers

    Atlas 200 Module Ascend Ai Board 8 Gb 128 Bits Lpddr4x 64mb Emmc 4.5 Ubuntu System

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    Brand Name : Hua Wei
    Model Number : Ascend Atlas 200
    Price : To be negotiated
    Payment Terms : L/C, D/A, D/P, T/T
    Supply Ability : Batch purchase price negotiation
    Delivery Time : 15-30 work days
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    Atlas 200 Module Ascend Ai Board 8 Gb 128 Bits Lpddr4x 64mb Emmc 4.5 Ubuntu System

    Ascend AI Board Atlas 200 Module 8 GB 128 bits LPDDR4X 64MB eMMC 4.5 Ubuntu System


    Hua Wei Ascend AI Board Atlas 200 Module

    OS:Ubuntu 16.04

    The Hua Wei Ascend Atlas 200 AI accelerator module has eight Cortex-A55 cores and provides common peripheral ports such as I2C, USB, SPI, and RGMII. It can be used as an embedded system CPU.You can burn the OS to the embedded multimedia controller (eMMC) flash or an SD card. After simple configuration, the ARM CPU in the Atlas 200 AI accelerator module can run users' AI service software.Generally, in this application mode, the Atlas 200 AI accelerator module is connected to simple external devices such as IP cameras (IPCs), I2C sensors, and Serial Peripheral Interface (SPI) displays.Powered by high-performance Huawei Ascend 310 AI Processor, the Atlas 200 AI accelerator module provides the 4 TFLOPS of FP16 and 8 TOPS for INT8, 8 TFLOPS of FP16 and 16 TOPS for INT8, as well as 11 TFLOPS of FP16 and 22 TOPS for INT8 multiply-add computing capabilities.

    Provides various interfaces and supports PCIe 3.0 x4, RGMII, USB 2.0/USB 3.0, I2C, SPI, and UART interfaces.

    Supports up to 16-channel 1080p@30 fps video access.

    Supports H.264 and H.265 video encoding and decoding in various specifications, which can be applicable to different video processing requirements.


    Hua Wei Ascend AI Board Atlas 200 Module Specification

    Feature

    Specification

    AI processor

    Ascend 310 AI Processor

    Two Da Vinci AI cores

    Eight A55 ARM cores (maximum frequency: 1.6 GHz)

    Memory

    8G 128 bits LPDDR4X


    Rate: 3200 Mbit/s

    Error checking and correcting (ECC)

    Storage

    Built-in SPI flash. Capacity: 64 MB

    External MMC interfaces and supports:

    – eMMC 4.5, supporting the highest-speed mode SDR50 and up to 64 GB capacity

    – SD3.0 card, supporting the highest-speed mode SDR50 and up to 2 TB capacity

    High-speed port

    One PCIe 3.0 x4, supporting the RC or EP mode

    One RGMII port

    One USB 3.0 port, compatible with USB 2.0

    Encoding/Decoding capability

    H.264/H.265 decoder, 20-channel 1080p (1920 x 1080) 25 FPS, YUV420

    H.264/H.265 decoder, 16-channel 1080p (1920 x 1080) 30 FPS, YUV420

    H.264/H.265 decoder, 2-channel 4K (3840 x 2160) 60 FPS, YUV420

    H.264/H.265 encoder, 1-channel 1080p (1920 x 1080) 30 FPS, YUV420

    JPEG decoding at 1080p (1920 x 1080) 256 FPS and encoding at 1080p (1920 x 1080) 64 FPS, up to 8192 x 4320 resolution

    PNG decoding at 1080p (1920 x 1080) 24 FPS, up to 4096 x 2160 resolution

    Temperature

    Operating temperature: -25°C to +80°C (-13°F to +176°F)

    Storage temperature: -25°C to +85°C (-13°F to +185°F)

    Other ports

    • One eMMC&SD port

    • ● Two PWM ports

    • ● Four GPIO ports

    Power consumption

    Operating voltage: 3.5 V to 4.5 V; recommended typical value: 3.8 V

    Typical power consumption

    – 4 GB: 6.5 W

    – 8 GB: 9.5 W

    FeatureSpecification

    Dimensions

    8.5 mm x 52.6 mm x 38.5 mm

    NOTE

    The connector model of the Atlas 200 AI accelerator module is fixed. You can select male connectors with different heights to determine the height of the Atlas 200 AI accelerator module.

    Net weight

    30g

    a: stable, maximum computing power.



    Basic software specifications

    Feature

    Specification

    Operating system (OS)

    Ubuntu 16.04

    Deep learning framework

    TensorFlow, Caffe

    Compiler

    CCE/CCE compiler Tool


    Atlas 200 Module Ascend Ai Board 8 Gb 128 Bits Lpddr4x 64mb Emmc 4.5 Ubuntu System

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