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❓ [Question] Is there any way to deploy on a single machine with multi-gpus? #3092

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SZ-ing opened this issue Aug 16, 2024 · 1 comment
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@SZ-ing
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SZ-ing commented Aug 16, 2024

❓ Question

What you have already tried

Environment

Build information about Torch-TensorRT can be found by turning on debug messages

  • PyTorch Version (e.g., 1.0):
  • CPU Architecture:
  • OS (e.g., Linux):
  • How you installed PyTorch (conda, pip, libtorch, source):
  • Build command you used (if compiling from source):
  • Are you using local sources or building from archives:
  • Python version:
  • CUDA version:
  • GPU models and configuration:
  • Any other relevant information:

Additional context

As the title, I have a machine with multiple GPUs and I would like to know if there is any way to evenly distribute the model across these GPUs. Is there any way to achieve this?

@SZ-ing SZ-ing added the question Further information is requested label Aug 16, 2024
@narendasan
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Take a look at these tutorials:

There are many tools out there to help convert a model to one that can run on multiple GPUs that can help automate this: https://www.deepspeed.ai/tutorials/automatic-tensor-parallelism/
https://huggingface.co/docs/accelerate/basic_tutorials/launch

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