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Adaptive multi-tier intelligent data manager for Exascale

Contributo in Atti di convegno
Data di Pubblicazione:
2023
Abstract:
The main objective of the ADMIRE project1 is the creation of an active I/O stack that dynamically adjusts computation and storage requirements through intelligent global coordination, the elasticity of computation and I/O, and the scheduling of storage resources along all levels of the storage hierarchy, while offering quality-of-service (QoS), energy efficiency, and resilience for accessing extremely large data sets in very heterogeneous computing and storage environments. We have developed a framework prototype that is able to dynamically adjust computation and storage requirements through intelligent global coordination, separated control, and data paths, the malleability of computation and I/O, the scheduling of storage resources along all levels of the storage hierarchy, and scalable monitoring techniques. The leading idea in ADMIRE is to co-design applications with ad-hoc storage systems that can be deployed with the application and adapt their computing and I/O behaviour on runtime, using malleability techniques, to increase the performance of applications and the throughput of the applications.
Tipologia CRIS:
04A-Conference paper in volume
Keywords:
High-Performance I/O; Malleability; Monitoring; Predictive models; Scheduling algorithms
Elenco autori:
Carretero J.; Garcia-Blas J.; Aldinucci M.; Besnard J.B.; Acquaviva J.-T.; Brinkmann A.; Vef M.-A.; Jeannot E.; Miranda A.; Nou R.; Riedel M.; Torquati M.; Wolf F.
Autori di Ateneo:
ALDINUCCI Marco
Link alla scheda completa:
https://iris.unito.it/handle/2318/1946991
Titolo del libro:
Proceedings of the 20th ACM International Conference on Computing Frontiers 2023, CF 2023
Progetto:
Third Party CINI - "ADMIRE - Adaptive multi-tier intelligent data manager for Exascale" - Call H2020-JTI-EuroHPC-2019-1 - Grant Agreement n. 956748 - CUP F69J21003450007
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