Method and System for Smarter Resource Management for Distributed Deep Learning
Page 01 of 4 Method and System for Smarter Resource Management for Distributed Deep LearningResource management in distributed deep learning requires new locality guarantees. Further, the workflow in distributed deep learning is not provided in map-reduce style. FIG. 1 illustrates an existing framework for resource management in distributed deep learning. Figure 1 As illustrated in FIG. 1, the resource management of the existing framework requires fairness and data locality and the distributed deep learning also requires parameter server (PS) – worker locality. Further, the existing framework requires manual task placement by a programmer and only provides static resource assignment to tasks. Disclosed is a method and system for an automated and smarter task assignment and role-aware placement of tasks to achieve high locality and performance for training of deep learning…
Link to Full Article: Method and System for Smarter Resource Management for Distributed Deep Learning
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