Treffer: A vulnerability factor for ECC-protected memory

Title:
A vulnerability factor for ECC-protected memory
Contributors:
Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
Publisher Information:
Institute of Electrical and Electronics Engineers (IEEE)
Publication Year:
2019
Collection:
Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge
Document Type:
Konferenz conference object
File Description:
6 p.; application/pdf
Language:
English
Relation:
https://ieeexplore.ieee.org/document/8854397; info:eu-repo/grantAgreement/AEI/RYC-2016-21104; info:eu-repo/grantAgreement/AGAUR/2017 SGR 1414; info:eu-repo/grantAgreement/AGAUR/2017-SGR-1328; info:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/; info:eu-repo/grantAgreement/EC/FP7/321253/EU/Riding on Moore's Law/ROMOL; info:eu-repo/grantAgreement/MINECO//SEV-2015-0493/ES/BARCELONA SUPERCOMPUTING CENTER - CENTRO. NACIONAL DE SUPERCOMPUTACION/; info:eu-repo/grantAgreement/EC/H2020/671697/EU/Mont-Blanc 3, European scalable and power efficient HPC platform based on low-power embedded technology/Mont-Blanc 3; info:eu-repo/grantAgreement/EC/H2020/779877/EU/Mont-Blanc 2020, European scalable, modular and power efficient HPC processor/Mont-Blanc 2020; info:eu-repo/grantAgreement/MINECO/2PE/RYC-2017-23269; http://hdl.handle.net/2117/186283
DOI:
10.1109/IOLTS.2019.8854397
Rights:
Open Access
Accession Number:
edsbas.DE514B84
Database:
BASE

Weitere Informationen

Fault injection studies and vulnerability analyses have been used to estimate the reliability of data structures in memory. We survey these metrics and look at their adequacy to describe the data stored in ECC-protected memory. We also introduce FEA, a new metric improving on the memory derating factor by ignoring a class of false errors. We measure all metrics using simulations and compare them to the outcomes of injecting errors in real runs. This in-depth study reveals that FEA provides more accurate results than any state-of-the-art vulnerability metric. Furthermore, FEA gives an upper bound on the failure probability due to an error in memory, making this metric a tool of choice to quantify memory vulnerability. Finally, we show that ignoring these false errors reduces the failure rate on average by 12.75% and up to over 45%. ; This work has been supported by the RoMoL ERC Advanced Grant (GA 321253), by the European HiPEAC Network of Excellence, by the Spanish Ministry of Economy and Competitiveness (contract TIN2015-65316- P), by the Generalitat de Catalunya (contracts 2017-SGR-1414 and 2017- SGR-1328), by the Spanish Government (Severo Ochoa grant SEV-2015- 0493) and by the European Union’s Horizon 2020 research and innovation programme (grant agreements 671697 and 779877). L. Jaulmes has been partially supported by the Spanish Ministry of Education, Culture and Sports under grant FPU2013/06982. M. Moreto and M. Casas have been partially supported by the Spanish Ministry of Economy, Industry and Competitiveness under Ramon y Cajal fellowships RYC-2016-21104 and RYC-2017-23269. ; Peer Reviewed ; Postprint (author's final draft)