Multiple context and/or multithreading

Description

I have one class and multiple objects of this class. Each object should do an inference. What are the options to do that?
I decided that each object has his own context. Is this right?
Also multithreading should be possible.

Are there some examples to this topic?

Environment

TensorRT Version: TensorRT-8.0.1.6_CUDA_11.3
GPU Type: Nvidia Titan RTX
Nvidia Driver Version:
CUDA Version: 11.3
CUDNN Version: 8.2.0
Operating System + Version: Windows 10
Python Version (if applicable):
TensorFlow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if container which image + tag):

Hi,

The below links might be useful for you.
https://docs.nvidia.com/deeplearning/tensorrt/archives/tensorrt-803/best-practices/index.html#thread-safety

https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__STREAM.html

For multi-threading/streaming, will suggest you to use Deepstream or TRITON
For more details, we recommend you raise the query in the Deepstream forum.
or
raise the query in the Triton Inference Server Github instance issues section.

Thanks!