document-understanding
2022.4
true
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Document Understanding User Guide
Automation CloudAutomation Cloud Public SectorAutomation SuiteStandalone
Last updated Oct 24, 2024

Hardware Requirements

Running the Document Understanding ML Packages on a GPU includes an optimization meant to accelerate the training process.

As a result, training on GPU is five times faster than on CPU (previously it was 10-20 times faster). This also makes it possible to train models on CPU with up to 5000 pages (previously it was 500 maximum).

Please be aware that training Document Understanding models on GPU requires a GPU with at least 11GB of video RAM to run successfully.

Use the below table to check the compatibility between the ML Packages, CUDA version, and GPU driver version.

ML Packages version

CUDA version

cudDNN version

NVIDIA driver (lowest compatible version)

Hardware Generation

2022.4

CUDA 11.3

cuDNN 8.2.0

R450.80.02

Ampere, Turing, Volta, Pascal, Maxwell, Kepler

CUDA is backward compatible, meaning that existing CUDA applications can continue to be used with newer CUDA versions.

More information about compatibility can be found here

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