TensorFlow Cluster
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A TensorFlow Cluster is a task set that participate in the distributed execution of a TensorFlow graph.
- See: TensorFlow Server, TensorFlow.
References
2017
- http://tensorflow.org/deploy/distributed
- QUOTE: A TensorFlow "cluster" is a set of "tasks" that participate in the distributed execution of a TensorFlow graph. Each task is associated with a TensorFlow "server", which contains a "master" that can be used to create sessions, and a "worker" that executes operations in the graph. A cluster can also be divided into one or more "jobs", where each job contains one or more tasks.
To create a cluster, you start one TensorFlow server per task in the cluster. Each task typically runs on a different machine, but you can run multiple tasks on the same machine (e.g. to control different GPU devices).
- QUOTE: A TensorFlow "cluster" is a set of "tasks" that participate in the distributed execution of a TensorFlow graph. Each task is associated with a TensorFlow "server", which contains a "master" that can be used to create sessions, and a "worker" that executes operations in the graph. A cluster can also be divided into one or more "jobs", where each job contains one or more tasks.