Abstract: Model partitioning is a promising technique for improving the efficiency of distributed inference by executing partial deep neural network (DNN) models on edge servers (ESs) or ...
Abstract: This paper presents a review of data partitioning and storage strategies critical for optimizing the performance and scalability of Artificial Intelligence (AI) and Machine Learning (ML) ...
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