LEGaTO: towards energy-efficient, secure, fault-tolerant toolset for heterogeneous computing

Cristal Kestelman, Adrián; Unsal, Osman S.; Martorell, Xavier; Carpenter, Paul Matthew; de la Cruz, Raul; Bautista Gomez, Leonardo; Jimenez, Daniel; Alvarez, Carlos; Salami, Behzad; Madonar, Sergi; Pericàs, Miquel; Trancoso, Pedro; von dem Berge, Micha; Billung-Meyer, Gunnar; Krupop, Stefan; Christmann, Wolfgang; Klawonn, Frank; Mihklafi, Amani; Becker, Tobias; Gaydadjiev, Georgi; Salomonsson, Hans; Dubhashi, Devdatt; Port, Oron; Etsion, Yoav; Nowack, Vesna; Fetzer, Christof; Hagemeyer, Jens; Jungeblut, Thorsten; Kucza, Nils; Kaiser, Martin; Porrmann, Mario; Pasin, Marcelo; Schiavoni, Valerio; Rocha, Isabelly; Göttel, Christian; Felber, Pascal

doi:10.1145/3203217.3205339

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Document typeConference lecture

Defense date2018-05-08

PublisherAssociation for Computing Machinery (ACM)

Rights accessOpen Access

All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder

ProjectLEGaTO - Low Energy Toolset for Heterogeneous Computing (EC-H2020-780681)

Abstract

LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.

CitationCristal, A. [et al.]. LEGaTO: towards energy-efficient, secure, fault-tolerant toolset for heterogeneous computing. A: "CF '18 Proceedings of the 15th ACM International Conference on Computing Frontiers". Association for Computing Machinery (ACM), 2018, p. 276-278.

URIhttp://hdl.handle.net/2117/120614

DOI10.1145/3203217.3205339

ISBN978-1-4503-5761-6

Publisher versionhttps://dl.acm.org/citation.cfm?id=3203217.3205339

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Computer Sciences - Ponències/Comunicacions de congressos [624]

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