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Ascend Atlas 200 Ai Accelerator Module 16 Tops 8 Gb 128 Bits 9.5 Watts Two Da Vinci Ai Core

    Buy cheap Ascend Atlas 200 Ai Accelerator Module 16 Tops 8 Gb 128 Bits 9.5 Watts Two Da Vinci Ai Core from wholesalers
     
    Buy cheap Ascend Atlas 200 Ai Accelerator Module 16 Tops 8 Gb 128 Bits 9.5 Watts Two Da Vinci Ai Core from wholesalers
    • Buy cheap Ascend Atlas 200 Ai Accelerator Module 16 Tops 8 Gb 128 Bits 9.5 Watts Two Da Vinci Ai Core from wholesalers
    • Buy cheap Ascend Atlas 200 Ai Accelerator Module 16 Tops 8 Gb 128 Bits 9.5 Watts Two Da Vinci Ai Core from wholesalers

    Ascend Atlas 200 Ai Accelerator Module 16 Tops 8 Gb 128 Bits 9.5 Watts Two Da Vinci Ai Core

    Ask Lasest Price
    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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    Ascend Atlas 200 Ai Accelerator Module 16 Tops 8 Gb 128 Bits 9.5 Watts Two Da Vinci Ai Core

    Ascend Atlas 200 AI Accelerator Module 16 TOPS 8 GB 128 bits 9.5 Watts Two Da Vinci AI core


    Hua Wei Ascend Atlas 200 AI Accelerator Module

    Packaged in a form factor half the size of a credit card, the Hua Wei Ascend Atlas 200 AI’s power consumption is as low as 9.5 Watts while supporting 16-channel real-time HD video analytics. This high-performance, low-power product can be deployed on devices such as cameras, drones, and robots.Powered by the Huawei Ascend AI processor, it supports real-time analytics of 16-channel HD videos in the size of half a credit card.Positioned for terminal devices such as cameras and drones, and edge devices such as AI edge stations, it has a Thermal Design Power (TDP) level of only 9.5W. 16TOPS INT8 @ 13W,16-channel HD video real-time analysis with JPEG decoding supported,8 GB memory | PCIe 3.0 x 4 lane interface,Operating temperature: -25°C to +80°C (-13°F to +176°F),144-pin board to board (BTB) connector


    Specifications about Hua Wei Ascend Atlas 200

    Feature

    Specification

    AI processor

    Ascend 310 AI Processor

    Two Da Vinci AI cores

    Eight A55 ARM cores (maximum frequency: 1.6 GHz)

    AI compute powera

    Half precision (FP16): 4/8/11 TFLOPS

    Integer precision (INT8): 8/16/22 TOPS

    Memory

    Type: LPDDR4X

    Bit width: 128 bits

    Capacity: 8 GB/4 GB

    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

    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

    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

    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

    Dimensions (H x W x D)

    8.5 mm x 52.6 mm x 38.5 mm (0.33 in. x 2.07 in. x 1.52 in.)

    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

    Operating system (OS)

    Ubuntu 16.04

    Deep learning framework

    TensorFlow, Caffe

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