Heterogeneous Secure Multi-level Remote Acceleration Service for Low-Power Integrated Systems and Devices

Lara López, Francisco Javier Nieto, Terpsichori-Helen Velivassaki, Sokol Kosta, Cheol-Ho Hong, Raffaele Montella, Iakovos Mavroidis, Carles Fernández

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
177 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)118-121
Number of pages4
JournalProcedia Computer Science
Volume97
DOIs
Publication statusPublished - 17 Oct 2016
EventCloud Futures: From Distributed to Complete Computing, CF2016, 18-20 October 2016, Madrid, Spain - Madrid, Spain
Duration: 18 Oct 201620 Feb 2017

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