An Optimal Resource Allocator of Elastic Training for Deep Learning Jobs on Cloud

Understand

Cloud training platforms, such as Amazon Web Services and Huawei Cloud provide users with computational resources to train their deep learning jobs.

• Elastic training is a service embedded in cloud training platforms that dynamically scales up or down the resources allocated to a job.
• The core technique of an elastic training system is to best allocate limited resources among heterogeneous jobs in terms of shorter queueing delay and higher training efficiency.
• This paper presents an optimal resource allocator for elastic training system that leverages a mixed-integer programming (MIP) model to maximize the training progress of deep learning jobs.