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

Some

1. Because of specific features of NVIDIA SDK

specific features allow

2. , neural analytics

to work only on Windows Server 2019 and Windows 10. Neural analytics

3. can work on

CPU, Nvidia GPU, VPU (Intel NCS, Intel HDDL).

4. GPU only in the operating systems specified in Operating system requirements. 

   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 on any computer that meets Axxon One hardware requirements (see Hardware requirements).

 We do not For Intel HDDL to work correctly with AMD processors, pre-install the OpenVINO™ toolkit version 2019.3.379 (see docs.openvino.ai

5. We don't recommend using more than one Intel NCS device per Server.

6. You can use several Intel HDDL devices on one Server if they have the same revisions.

7. Neural analytics can work on the following devices: CPU, Nvidia GPU, VPU (Intel NCS).

8. If CPU or Intel GPU is used to run analytics, the following requirements 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 tools

9. 1. 1. detectors 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 must support the Intel CPU that you use (see software.intel.com).
   3. CPU must support the AVX2 or AVX512 instruction set (see ark.intel.com).
10. NVIDIA GeForce 1050 Ti graphics card or higher. Requirements:
    1. At least 2 GB of memory;
    2. CUDA 11.1
–11.4
11. 1. or higher;

    2. Compute Capability 3.5

–8

12. 1. or higher.

6.

13. 1. Note
       title Attention!
       CUDA is compatible with generations of computers with the following architectures: Kepler (partially), Maxwell, Pascal, Volta, Turing, Ampere, Ada Lovelace (partially) (

see 

14. 1. 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.

We recommend using AxxonSoft Platform Calculator (see AxxonSoft Platform Calculator documentation) to calculate the required video memory for detectors that use neural networks (see General information on neural analytics).

When you use a graphics card, a single neural network requires 500 MB of video memory, except for the neural network for Face Detection (see Hardware requirements for the Face Detection TV and its sub-tools) and License Plate Recognition RR (see Hardware requirements for License 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 graphics cards in your system.