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mreso committed Mar 29, 2023
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1 change: 1 addition & 0 deletions docs/contents.rst
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model_zoo
request_envelopes
server
mps
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sphinx/requirements
torchserve_on_win_native
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1 change: 1 addition & 0 deletions docs/index.md
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* [TorchServe on Kubernetes](https://github.com/pytorch/serve/blob/master/kubernetes/README.md#torchserve-on-kubernetes) - Demonstrates a Torchserve deployment in Kubernetes using Helm Chart supported in both Azure Kubernetes Service and Google Kubernetes service
* [mlflow-torchserve](https://github.com/mlflow/mlflow-torchserve) - Deploy mlflow pipeline models into TorchServe
* [Kubeflow pipelines](https://github.com/kubeflow/pipelines/tree/master/samples/contrib/pytorch-samples) - Kubeflow pipelines and Google Vertex AI Managed pipelines
* [NVIDIA MPS](mps.md) - Use NVIDIA MPS to optimize multi-worker deployment on a single GPU
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# Enabling NVIDIA MPS in TorchServe
# Running TorchServe with NVIDIA MPS
In order to deploy ML models, TorchServe spins up each worker in a separate processes, thus isolating each worker from the others.
Each process creates its own CUDA context to execute its kernels and access the allocated memory.

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