GTC Silicon Valley-2019: Dask and V100s for Fast, Distributed Batch Scoring of Computer Vision Workloads
GTC Silicon Valley-2019 ID:S9198:Dask and V100s for Fast, Distributed Batch Scoring of Computer Vision Workloads
Danielle Dean(Microsoft),Mathew Salvaris(Microsoft)
A common deep learning workload is batch processing of videos to identify objects an image. We'll show examples of how to deploy a style-transfer and object-detection model on a cluster of V100 GPUs using Dask. Dask allows us develop the logic of our processing pipeline locally and deploy it on a cluster without having to rewrite anything. We'll discuss how we integrate it into Azure ML pipelines, as well as how to deploy it on a Kubernetes cluster for a scalable solution.