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Enabling microservices management for Deep Learning applications across the Edge-Cloud Continuum
2021
2021 IEEE 33rd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)
Deep Learning has shifted the focus of traditional batch workflows to data-driven feature engineering on streaming data. In particular, the execution of Deep Learning workflows presents expectations of near-real-time results with user-defined acceptable accuracy. Meeting the objectives of such applications across heterogeneous resources located at the edge of the network, the core, and in-between requires managing trade-offs between the accuracy and the urgency of the results. However, current
doi:10.1109/sbac-pad53543.2021.00025
fatcat:oud6hcplpnbn5eydwm6up2azvq