# NVIDIA® GPU Requirements

The following information covers the requirements when utilizing an NVIDIA GPU with your ViDi application. The GPU is utilized by ViDi during the development of your application, typically with the training of tools. In addition, a GPU can also be used during runtime deployment, where it increase performance of runtime workspaces.

Note:

- While technically a GPU is not required, it greatly improves the speed and performance while training ViDi tools. Therefore, Cognex highly recommends the use of a GPU.

## NVIDIA Driver Support

- NVIDIA GeForce® driver greater than or equal to 431.86 (Creator Ready)

- NVIDIA Quadro® driver greater than or equal to 431.94 (Optimal Driver for Enterprise)

  Note: For more information about supported drivers, please visit the Cognex Support Site.

## Supported NVIDIA GPUs

GPU | Model | Performance Level | System Power Supply
--- | --- | --- | ---
NVIDIA GeForce® | GTX 1060 | Low to Medium | ≥ 500W
GTX 1070 | Medium | ≥ 600W
GTX 1080 Ti | High | ≥ 600W
RTX™ 2070 | Medium | ≥ 550W
RTX 2080 | Medium to High | ≥ 650W
RTX 2080 Ti | High | ≥ 650W
NVIDIA Quadro® | P2000 | Low | ≥ 500W
P4000 | Medium to High | ≥ 600W
GV100* | High | ≥ 600W
RTX 4000 | Medium | ≥ 550W
RTX 5000 | Medium to High | ≥ 650W
RTX 6000 | High | ≥ 650W
RTX 8000 | High | ≥ 650W
Titan V* | High | ≥ 600W
Titan RTX | High | ≥ 650W
NVIDIA Tesla® | P5000 | High | ≥ 600W
V100* | High | ≥ 600W
Note: When selecting a GPU, Cognex only supports NVIDIA GPUs. Consider the following when choosing an NVIDIA GPU: At a minimum, an NVIDIA® CUDA® enabled GPU. When selecting an NVIDIA GPU, a unit with a higher core clock frequency, CUDA cores and Tensor cores will result in faster computational speeds. Due to this, Cognex strongly recommends the use of NVIDIA Quadro and Tesla GPUs for the following reasons: These GPUs support the compute-optimized Tesla Compute Cluster (TCC) mode. These GPUs are designed and tested for continuous duty-cycle operation. These GPUs undergo rigorous testing and qualification by NVIDIA. ViDi 4.1.0 supports the use of any NVIDIA CUDA® enabled GPU that provides a compute capability of 3.0 and higher, and requires a driver version greater than or equal to 431.86. CUDA compute capability 3.0 or higher is required to use the core ViDi functionality. The Low Precision parameter requires CUDA compute capability 6.1 or higher (for more information, visit the NVIDIA website). A minimum of 4 GB of GPU memory is required for runtime operation, and a minimum of 8 GB of GPU memory is required for training. The NVIDIA GeForce Titan V, Quadro GV100 and Tesla V100 include NVIDIA Tensor Cores. ViDi 4.1.0 will automatically utilize Tensor Cores if they are present, provided you have a Standard or Advanced security license. Please contact your Cognex Sales Representative for information about enabling the functionality on your Cognex Security Dongle.