Containerizing Deep Learning Workloads on Xeon Phi Cluster for AI Web Applications
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AI Web App jobs require a scheduler to process Deep learning workloads. Docker containers execute these workloads in Xeon Phi Clusters. ...learn more
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Student Developers for AI
Overview / Usage
Today's Web applications are data intensive and demand environments like tensorflow to execute the workloads. Hence, Containers are best suited to provide the framework and compute resources like CPU and memory for each workload. It decouples the app environment from the running machine/host and encapsulates all dependencies in a single portable unit. Nomad is a state of the art tool for scheduling Docker Containers. Test Model Workload is generated from Model Zoo for each framework.