Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4962116 | Procedia Computer Science | 2016 | 4 Pages |
Abstract
This position paper presents a novel heterogeneous CPU-GPU multi-level cloud acceleration focusing on applications running on embedded systems found on low-power devices. A runtime system performs energy and performance estimations in order to automatically select local CPU-based and GPU-based tasks that should be seamlessly executed on more powerful remote devices or cloud infrastructures. Moreover, it proposes, for the first time, a secure unified model where almost any device or infrastructure can operate as an accelerated entity and/or as an accelerator serving other less powerful devices in a secure way.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Lara López, Francisco Javier Nieto, Terpsichori-Helen Velivassaki, Sokol Kosta, Cheol-Ho Hong, Raffaele Montella, Iakovos Mavroidis, Carles Fernández,