Binary Tree Classification of Rigid Error Detection and Correction Techniques Angeliki Kritikakou, Rafail Psiakis, Francky Catthoor, Olivier Sentieys
Binary Tree Classification of Rigid Error Detection and Correction Techniques Angeliki Kritikakou, Rafail Psiakis, Francky Catthoor, Olivier Sentieys To cite this version: Angeliki Kritikakou, Rafail Psiakis, Francky Catthoor, Olivier Sentieys. Binary Tree Classification of Rigid Error Detection and Correction Techniques. ACM Computing Surveys, Association for Com- puting Machinery, 2020, 53 (4), pp.1-38. 10.1145/3397268. hal-02927439 HAL Id: hal-02927439 https://hal.archives-ouvertes.fr/hal-02927439 Submitted on 29 Jan 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 1 Binary Tree Classification of Rigid Error Detection and Correction Techniques ANGELIKI KRITIKAKOU, Univ Rennes, Inria, CNRS, IRISA, France RAFAIL PSIAKIS, Univ Rennes, Inria, CNRS, IRISA, France FRANCKY CATTHOOR, IMEC, KU Leuven, Belgium OLIVIER SENTIEYS, Univ Rennes, Inria, CNRS, IRISA, France Due to technology scaling and harsh environments, a wide range of fault tolerant techniques exists to deal with the error occurrences. Selecting a fault tolerant technique is not trivial, whereas more than the necessary overhead is usually inserted during the system design. To avoid over-designing, it is necessary to in-depth understand the available design options. However, an exhaustive listing is neither possible to create nor efficient to use due to its prohibited size.
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