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Hardware The hardware requirements for the neural analytics (see General information on neural analytics) are the following:

1. Some NVIDIA SDK specific features allow the neural analytics to work only on Windows Server 2019 or and Windows 10. 

2. For neural analytics operation, you may use Neural analytics can work on CPU, Nvidia GPU NVIDIA, VPU (Intel NCS, Intel  Intel HDDL).

   Note
   title Attention!
   To connect Intel NCS, insert the device into a USB port and make sure that it is recognized by Windows OS as a USB device with one of the following names: Movidius, Myriad X, or VSC Loopback Device. You can use Intel NCS may be used with any PC on any computer that meets Axxon One hardware requirements (see Hardware requirements).We  We do not recommend using more than one Intel NCS device per Server. You can use several Intel HDDL devices on the one Server if they have the same revisions. For Intel HDDL to work correctly with AMD processors, pre-install the OpenVINO™ toolkit version 2019.3.379 (see docs.openvino.ai).

   
   

3. If the detection tool uses CPU or Intel GPU resourcesis used to run analytics, the following requirements should must be met:

   1. Supported CPUs:

      1. 6th Generation Intel® Core™ processors and higher;.

         Note
         title Attention!
         When using a CPU lower than 6th Generation Intel® Core™ processors, the operation of the detection tool is not tools isn't guaranteed.

         
         

      2. Intel® Xeon® v5 family ;and Intel® Xeon® v6 family;.
      3. Intel® Movidius™ Neural Compute Stick;.
      4. Intel® Neural Compute Stick 2;.
      5. Intel® Vision Accelerator Design with Intel® Movidius™ VPUs.
   2. OpenVino should must support the Intel CPU in that you use (see https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit/system-requirements.html).
   3. CPU should must support the AVX2 or AVX512 instruction set (see https://see ark.intel.com/content/www/us/en/ark/search/featurefilter.html?productType=873&1_Filter-InstructionSetExtensions=3533&1_Filter-Family=595).
4. Video card: NVIDIA GeForce 1050 Ti or Ti grahics cardor higher. Requirements:
   1. At least 2 GB of memory;
   2. CUDA 11.1—111–11.4;

   3. Compute Capability 3.5—85–8.6.

      Note
      title Attention!
      CUDA is compatible with generations of computers with the following architectures: Kepler (partially), Maxwell, Pascal, Volta, Turing, Ampere (partially) (see CUDA). You can check Compute Capability GPU version on the manufacturer's website. If you use NVIDIA graphics cards, make sure to download the latest drivers from the manufacturer's website.

When using you use a video graphics card, a single neural network requires 500 MB of video memory, except for the neural network for face detection Face Detection (see Hardware requirements for face detection) and license plate recognition (RR) the Face Detection TV and its sub-tools) and License Plate Recognition RR (see Hardware requirements for License plate recognition (Plate Recognition RR and Vehicle Recognition RR)). For example: a neural fire detection tool and a neural smoke detection tool, both with unlimited number of channels, require a 1 GB graphics card or higher. You can use multiple video graphics cards in your system.

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