Putting Data Science Pipelines on the Edge

Ali Akoglu (1) , Genoveva Vargas-Solar (2)

1 University of Arizona
2 BD - Base de Données

This paper proposes a composable "Just in Time Architecture" for Data Science (DS) Pipelines named JITA-4DS and associated resource management techniques for configuring disaggregated data centers (DCs). DCs under our approach are composable based on vertical integration of the application, middleware/operating system, and hardware layers customized dynamically to meet application Service Level Objectives (SLO-application-aware management). Thereby, pipelines utilize a set of flexible building blocks that can be dynamically and automatically assembled and reassembled to meet the dynamic changes in the workload's SLOs. To assess disaggregated DC's, we study how to model and validate their performance in large-scale settings.

Mots clés: Disaggregated Data Centers; Data Science Pipelines; Edge Computing

Domaines: Base de données [cs.DB]

Ali Akoglu, Genoveva Vargas-Solar. Putting Data Science Pipelines on the Edge. 1st International Workshop on Big data driven Edge Cloud Services, May 2021, Biarritz, France. ⟨10.1007/978-3-030-92231-3_1⟩. ⟨hal-03183518⟩