GPU Requirements

Either a CUDA (12 or later) or an OpenCL driver (1.2 or later) for the GPU is necessary to use Zivid.

• For Windows, the driver is usually installed together with the graphics driver: NVIDIA, Intel.

• For Linux, install the GPU driver for your backend: see About GPU for installing the NVIDIA driver (CUDA backend) or the OpenCL driver.

Follow the instructions on how to check whether you have OpenCL. For the CUDA backend, check that nvidia-smi reports an NVIDIA driver that supports CUDA 12 or later.

Dedicated GPU

A dedicated GPU gives the best performance with Zivid. It is also the best choice if the GPU will be used for more than Zivid’s computations. A medium to high-end NVIDIA GPU with at least 3 GB of memory is required for optimal performance. This is the preferred solution for Zivid.

Requirements:

• NVIDIA GPUs must meet a minimum compute capability, which differs between the two compute backends:

  • CUDA backend: compute capability 6.1 or higher. This covers the GTX 10-series and everything newer, so cards from 2016 onwards. The exception lists the compute capabilities the installed package was built for:

    Detected compute capability X.Y, which is not supported. Supported versions: (6.1, 7.0, 7.5, 8.0, 8.6)

    Setting AllowUnsupported does not make the CUDA backend work below this minimum. The packages contain no code for older architectures, so the capture fails later instead. Use a newer GPU, or the OpenCL version of the SDK.

  • OpenCL backend: no practical limit. The requirement is OpenCL 1.2 support, which every NVIDIA card new enough to have an OpenCL driver provides. A compute capability floor of 3.5 exists in the SDK, but no driver that meets the OpenCL requirement falls below it, so in practice the OpenCL version covers the full range of NVIDIA cards:

    The compute capability X.Y of the Nvidia compute device is lower than the minimum required compute capability 3.5. Update to a supported compute device by consulting <link>.

  A GPU below 6.1 therefore works with the OpenCL backend but not with the CUDA backend. Be aware that the OpenCL version of the SDK rejects every NVIDIA GPU regardless of compute capability until you opt in to unsupported compute devices in the Config.yml file. The 3.5 minimum applies only once that opt-in is in place.

  On Jetson the CUDA package is built for the compute capability of the Jetson hardware itself, so this minimum does not apply, and the OpenCL version is not available. See Install Zivid on Jetson Linux.

  NVIDIA GPU 및 해당 compute capability에 대한 개요는 https://developer.nvidia.com/cuda-gpus 에서 찾을 수 있습니다.

Recommendations:

• NVIDIA GeForce GTX 1060 or newer for desktops

• NVIDIA GeForce MX150 or newer for laptops

  조심

  SDK 2.10부터 Ubuntu 18.04에 대한 지원이 종료되었습니다. 이전 SDK 버전에 대한 Ubuntu 18.04 지침을 보려면 왼쪽 상단 모서리에서 기술 자료 버전을 변경하십시오.

CPU with integrated GPU

This is the most cost-efficient solution for Zivid. The benefit of an integrated GPU is that the data transfer from GPU to CPU is fast. It is also beneficial for applications that require low power consumption, e.g., battery-powered mobile platforms. A high-end integrated GPU with at least 3 GB of memory available is required for optimal performance.

Recommendations:

• HD630 이상의 Intel i7

  조심

  SDK 2.10부터 Ubuntu 18.04에 대한 지원이 종료되었습니다. 이전 SDK 버전에 대한 Ubuntu 18.04 지침을 보려면 왼쪽 상단 모서리에서 기술 자료 버전을 변경하십시오.

팁

저전력 소비가 필요한 애플리케이션에 CPU with integrated GPU 를 사용을 추천합니다. 예: battery powered mobile platforms with cameras.

Version History

SDK	Changes
2.18.0	Added support for the CUDA compute backend for NVIDIA GPUs.
2.11.0	AMD는 더 이상 권장되지 않습니다. SDK에서 공식 지원이 종료되었습니다. Enable Unsupported Compute Device for Zivid Software 을 참조하세요.
2.10.0	Ubuntu 18.04 지원이 종료되었습니다.