Abstract:Hybrid distributed computing software architectures gain great importance in data analysis workflows as the number of available underlying machine learning libraries and data storage systems increase. We argue that there is a need for novel approaches for software architecture designs that can enable machine learning data analysis workflows to run on top of different subsystem libraries. To address this need, we propose a hybrid distributed software architecture in this manuscript. The proposed architecture ma… Show more
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