I want to across compile the tensorrt sample code for aarch64 in a x86_64 machine.
I used the SDK manager 18.104.22.16874 software to install CUDA in the host machine. It can not find the related TensorRT and cuDNN softwares. When I build the demo trtexec, I got some errors about that can not found some lib files. I find that the same name lib in the x86_64 target, but it is not in the aarch64 target.
I use a PC without nvidia platform GPU.
I want to install the related software about Tensorrt and cudnn.
some one would give me some guide?
Thanks for your time.
There are some information about the CUDA libs with SDK Manager installed
In the x86_64
in the aarch64
There are different library between x86_64 and aarch64 platform. When I build the TensorRT sample trtexec code, I got the error.
There are some libs need by the code exist in the x86_64 but don’t exist in the aarch64 platform.
So should I reinstall CUDA aarch64 version manual in the x86_64 platform?
The sample code also need the TensorRT libs, should I install Tensorrt aarch64 in the x86_64 platform ? How I get it ?
Thanks for your times.
Since there are lots of dependencies to cross-compile a TensorRT software.
Please use our docker container for the environment setup.
You can find the detailed steps below:
thanks for your reply.
I also have some questions about the
README.md in the project
There are some contents.
(Optional) JetPack SDK for Jetson builds Using the JetPack SDK manager, download the host components. Steps: Download and launch the SDK manager. Login with your developer account. Select the platform and target OS (example: Jetson AGX Xavier, Linux Jetpack 4.4), and click Continue. Under Download & Install Options change the download folder and select Download now, Install later. Agree to the license terms and click Continue. Move the extracted files into the <TensorRT-OSS>/docker/jetpack_files folder.
I got some
.deb ubuntu install package through sdkmanager. I would like to know which files should to be extracted and then move to the releated folder.
You can find the required file below:
cuda-repo-cross-aarch64\*.deb cuda-repo-ubuntu\*_amd64.deb libcudnn[7-8]_\*-1+cuda10.[0-9]_arm64.deb ...
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