What dependencies are needed to deploy TensorRT7 for Windows platform as a portable application

Description

As stated in the post
I’m planning to deploy TensorRT7 as a dll plugin for a portable application on Windows platform, and I found out by looking at the VS calls that TensorRT actually calls a lot of dll files from the CUDA\bin directory, and I think I can only install CUDA to run the TensorRT portable application.
My question is, is it possible to satisfy a portable application with a minimum of dll dependencies? Not by installing CUDA

Environment

TensorRT Version: 7.2.2.3
GPU Type: RTX 3080
Nvidia Driver Version: 470.05
CUDA Version: 11.1
CUDNN Version: 8.0
Operating System + Version: Windows 10 21343

Relevant Files

Steps To Reproduce

Please include:

  • Exact steps/commands to run your repro
    Write a TensorRT application, generate it as a dll file, and call it through an external program
  • Full traceback of errors encountered
    If CUDA is not installed, it will not run, indicating that nvinfer.dll cannot be found.

Hi,
Please refer to the installation steps from the below link if in case you are missing on anything
https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html
Also, we suggest you to use TRT NGC containers to avoid any system dependency related issues.
https://ngc.nvidia.com/catalog/containers/nvidia:tensorrt

Thanks!

Thank for your reply
We can install and run TensorRT for Windows platform on our model properly, but we are aiming to deploy on Windows platform and need to consider the case where CUDA is not installed.

However, I tried copying the dll from the CUDA\bin directory that the project needs to the project’s lib folder, then deleting CUDA from Path and adding only the project’s lib directory to Path, which does run and does not require CUDA to be installed on Windows

Hi @851482801,

We have a tool Dependency Walker, which may help you.
https://www.dependencywalker.com/

Thank you.

Thank you, I have found the dependencies, the only problem should be that the dependency files are too big for easy deployment.

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