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Sustainable Performance for High-Performance Embedded Computing Systems

Total Cost €


EC-Contrib. €






Project "SuPerCom" data sheet

The following table provides information about the project.


Organization address
address: Calle Jordi Girona 31
postcode: 8034

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Project website
 Total cost 1˙998˙918 €
 EC max contribution 1˙998˙918 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2017-COG
 Funding Scheme ERC-COG
 Starting year 2018
 Duration (year-month-day) from 2018-06-01   to  2023-05-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Computers increasingly intervene in critical aspects of our life related to health, safety, and security, resulting in (critical) software controlling functionalities or services with humans in the loop. This trend towards critical-function digitization brings huge benefits for society and rests two pillars: the use of high-performance parallel hardware as the only viable option to cover the highest-ever critical software’s performance needs; and the ability to provide sustainable (guaranteed) performance, instead of average unreliable performance. Failing to support both pillars prevents embedded computers from safely executing critical software potentially causing unacceptable risks or threats to human life. SuPerCom goes beyond current solutions, which face either major scalability limitations or cannot provide performance guarantees, and proposes a holistic multidisciplinary approach that addresses the challenge of providing high and sustainable performance with future embedded computers comprising high-performance hardware with unprecedented complexity levels. SuPerCom synergistically combines for the first time performance analysis, hardware design and statistical and machine learning techniques. With SuPerCom performance predictability and performance observability become first-class citizen hardware requirements, rather than being considered at the end of the design. SuPerCom also proposes statistical and machine-learning techniques to (i) deal with big amounts of performance data coming from hardware sensors and (ii) provide on-line optimizations to increase sustainable performance. SuPerCom breakthrough can have significant economic and societal impact by allowing embedded computers to use high-performance hardware with strong guarantees of sustainable performance. This, in turn, will allow executing a wide-variety of performance-demanding critical software like advanced driver assistance systems in cars or advanced medical devices with sound guarantees.


year authors and title journal last update
List of publications.
2019 Pedro Benedicte, Carles Hernandez, Jaume Abella, Francisco J. Cazorla
Locality-aware cache random replacement policies
published pages: 48-61, ISSN: 1383-7621, DOI: 10.1016/j.sysarc.2018.12.007
Journal of Systems Architecture 93 2020-02-20
2018 Jordi Cardona, Carles Hernandez, Jaume Abella, Francisco J. Cazorla
EOmesh: Combined Flow Balancing and Deterministic Routing for Reduced WCET Estimates in Embedded Real-Time Systems
published pages: 2451-2461, ISSN: 0278-0070, DOI: 10.1109/TCAD.2018.2857298
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 37/11 2020-02-20
2018 Sergi Alcaide, Leonidas Kosmidis, Hamid Tabani, Carles Hernandez, Jaume Abella, Francisco J. Cazorla
Safety-Related Challenges and Opportunities for GPUs in the Automotive Domain
published pages: 46-55, ISSN: 0272-1732, DOI: 10.1109/MM.2018.2873870
IEEE Micro 38/6 2020-02-20
2019 Giesen, Jeremy; Mezzetti, Enrico; Abella, Jaume; Fernández, Enrique; Cazorla, Francisco J.
ePAPI: Performance Application ProgrammingInterface for Embedded Platforms
published pages: , ISSN: , DOI: 10.4230/OASIcs.WCET.2019.3
2019 Pujol, Roger; Tabani, Hamid; Kosmidis, Leonidas; Mezzetti, Enrico; Abella, Jaume; Cazorla, Francisco J.
Generating and Exploiting Deep Learning Variants to Increase Heterogeneous Resource Utilization in the NVIDIA Xavier
published pages: , ISSN: , DOI: 10.4230/LIPIcs.ECRTS.2019.23

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The information about "SUPERCOM" are provided by the European Opendata Portal: CORDIS opendata.

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