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APwML-Hackathon-Distributed-Inference

Status after hackathon

There are two important tools completed and ready to be modified for more general use.

  • run_tritonserver.py creates a triton server using condor, inside a singularity. You can create many servers (input of the function needs some more attention). The function returns the ip address of the servers created, to be used by clients.

  • client_wrapper.py recieves an ip address and a model name already used in the triton servers and it creates a client and a queue object. Then it sends inference requests and gets back the result, dumped inside the queue.

    For model_repo and model data mly models were used.

## Possible next steps

  • Creating workers that will run the client and the inference requests using condor

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