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When you use neural analytics (see see General information on neural analytics), the hardware requirements are the following:
- Some
- Take into account the limitations of NVIDIA SDK specific features allow
- . The neural analytics to work only on Windows Server 2019 and Windows 10.
- can operate on the GPU only in the operating systems specified in the Operating system requirements page. 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:
- VPU requirements (Intel NCS):
- Connect a device to the computer USB port.
- Make sure that the Windows system identifies a device as
- 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 recommend using - Use it on the computers that meet the Hardware requirements.
- Apply no more than one Intel NCS device
per Server.You can use several Intel HDDL devices - on
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).
- the server.
Supported CPUs:- Intel® Xeon® v5 family and Intel® Xeon® v6 family.
- Intel® Movidius™ Neural Compute Stick.
- Intel® Neural Compute Stick 2. Intel®
- Supported CPUs and requirements:
CPU type Supported generations/models Key requirements and conditions Intel® Core™ 6th generation (Skylake) and higher - Support for the AVX2 or AVX512 instruction set (see ark.intel.com)
- We don't guarantee the detector operation on CPUs lower than 6th generation
Intel® Xeon® Families v5 (Broadwell) and v6 (Skylake) - Support for the AVX2 or AVX512 instruction set (see ark.intel.com).
- CPU compatibility with the OpenVINO toolkit version that you use (see software.intel.com)
Intel VPU devices Movidius™ Neural Compute Stick, Neural Compute Stick 2, Vision Accelerator Design with Intel® Movidius™ VPUs .Support from the OpenVINO toolkit version that you use (see software.intel.com) .- CPU must support the AVX2 or AVX512 instruction set (see ark.intel.com). NVIDIA GeForce 1050 Ti grahics cardor higher. Requirements:
- At least 2 GB of memory;
- CUDA 11.1–11.4;
- Requirements for NVIDIA GPU:
Parameter Minimum/recommended requirements GPU model - NVIDIA GeForce GTX 1050 and later (for Detector Pack 3.14–3.15.1)
- NVIDIA GeForce GTX 1650 and later (for Detector Pack 3.15.2 and later)
Video memory space At least 2 GB. For the accurate calculation, we recommend using AxxonSoft Platform Calculator (see AxxonSoft Platform Calculator documentation) CUDA version - 11.1–11.8 (for Detector Pack 3.14–3.15.1)
- 12.8.1 (for Detector Pack 3.15.2 and later)
Compute Capability - 6.0–9.0 (for Detector Pack 3.14–3.15.1)
- 7.5–12.0 (for Detector Pack 3.15.2 and later)
You can check the version here or on the manufacturer's website
Supported architectures - Kepler (late
CUDA is compatible with generations of computers with the following architectures: Kepler (partially - ), Maxwell, Pascal, Volta, Turing, Ampere, Ada Lovelace (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.
Neural analytics can work on CPU, Nvidia GPU, VPU (Intel NCS, Intel HDDL).
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If CPU or Intel GPU is used to run analytics, the following requirements must be met:
6th Generation Intel® Core™ processors and higher.
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When using a CPU lower than 6th Generation Intel® Core™ processors, the operation of the detection tools isn't guaranteed. |
Compute Capability 3.5–8.6.
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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.
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- (for Detector Pack 3.14–3.15.1)
- Turing, Ampere, Ada Lovelace (partially), Hopper, and Blackwell (for Detector Pack 3.15.2 and later)
- In Windows OS, starting with the Detector Pack 3.15.2 version, the support for Hopper and Blackwell is added for the following detectors:
Drivers We recommend installing the latest driver version from the official website Configuration You can use up to four GPUs on one server - For the correct operation, each detector must meet individualspecificrequirements (see Detectors) to:
- Hardware platform,
- Video stream and scene,
- Image characteristics.