You have an Azure Machine Learning workspace. You build a deep learning model.
You need to publish a GPU-enabled model as a web service.
Which two compute targets can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
To publish a GPU-enabled model as a web service in Azure Machine Learning, you can use Azure Kubernetes Service (AKS) and Azure Machine Learning compute clusters. AKS supports GPU-enabled deployments and is suitable for hosting scalable and reliable web services. Azure Machine Learning compute clusters can also be used to deploy models as a managed web service, providing a scalable environment for GPU-based models. Azure Container Instances (ACI) is generally used for lower-scale CPU-based workloads and does not support GPU-based deployments for web services.
Azure Container Instances (ACI) does support GPU-based deployments, which can be used to accelerate the execution of deep learning models. You can use ACI to deploy a GPU-enabled model as a web service in an Azure Machine Learning workspace. Regarding Azure Machine Learning compute clusters, you are also correct that they cannot be used as a deployment target for web services. Compute clusters are used for training and batch scoring workloads, not for deploying models as web services. In summary, the correct answer to your question is A. Azure Kubernetes Service (AKS) and B. Azure Container Instances (ACI). Check the link: https://learn.microsoft.com/en-us/azure/container-instances/container-instances-gpu SaM
answer is AD.
Answer - AD Azure Compute Instances do not support GPU, only use for low-scale CPU-based workloads. Reference https://learn.microsoft.com/en-us/azure/machine-learning/concept-compute-target?view=azureml-api-2
B. Azure Container Instances (ACI) not Azure Compute Instances
Answer AD
this is correct
well, i think its AB.
AB correct
ACI doesn't support GPU