.engine generated on device A can`t be deployed to device B

AI & Data Science Deep Learning (Training & Inference) TensorRT
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Description

A clear and concise description of the bug or issue.

Environment

TensorRT Version: 7.2.2-1
GPU Type: GeForce GTX 1650 Ti Mobile
Nvidia Driver Version: 525.85.12
CUDA Version: 11.1
CUDNN Version: 8.0.5.39
Operating System + Version: Linux 22.04
Python Version (if applicable):
TensorFlow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if container which image + tag):

Relevant Files

Please attach or include links to any models, data, files, or scripts necessary to reproduce your issue. (Github repo, Google Drive, Dropbox, etc.)

Steps To Reproduce

I did generated an YOLOv4 .engine file on a given system. However, .engine does not work in similar setup, where just the GPU differs (RTX3080 8GB).
Maybe, you have suggestions why this happens?

Thanks in advance!

2

Engines aren’t supposed to work on different devices. Maybe you can build engine with hardware compatibility Developer Guide :: NVIDIA Deep Learning TensorRT Documentation, but I think it can hurt performance

3

Thanks!
I also found some additional information Developer Guide :: NVIDIA Deep Learning TensorRT Documentation

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