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AdAM: Adaptive Approximate Multiplier for Fault Tolerance in DNN AcceleratorsTaheri, Mahdi; Cherezova, Natalia; Nazari, Samira; Azarpeyvand, Ali; Ghasempouri, Tara; Daneshtalab, Masoud; Raik, Jaan; Jenihhin, MaksimIEEE transactions on device and materials reliability2024 / p. 66-75 : ill https://doi.org//10.1109/TDMR.2024.3523386

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Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine

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AdAM: adaptive fault-tolerant approximate multiplier for edge DNN acceleratorsTaheri, Mahdi; Cherezova, Natalia; Nazari, Samira; Rafiq, Ahsan; Azarpeyvand, Ali; Ghasempouri, Tara; Daneshtalab, Masoud; Raik, Jaan; Jenihhin, Maksim2024 IEEE European Test Symposium (ETS): ETS 2024 : May 20-24, 2024, The Hague, Netherlands : proceedings2024 https://doi.org/10.1109/ETS61313.2024.10567161 Conference Proceedings at Scopus Article at Scopus Article at WOS

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Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine

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book article

APPRAISER : DNN fault resilience analysis employing approximation errorsTaheri, Mahdi; Ahmadilivani, Mohammad Hasan; Jenihhin, Maksim; Daneshtalab, Masoud; Raik, Jaan2023 26th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)2023 / p. 124−127 : ill https://ddecs2023.taltech.ee/ https://doi.org//10.1109/DDECS57882.2023.10139468

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Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine

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book article

DeepAxe : a framework for exploration of approximation and reliability trade-offs in DNN acceleratorsTaheri, Mahdi; Riazati, Mohamad; Ahmadilivani, Mohammad Hasan; Jenihhin, Maksim; Daneshtalab, Masoud; Raik, Jaan; Sjödin, Mikael; Lisper, Björn2023 24th International Symposium on Quality Electronic Design (ISQED)2023 / 8 p. : ill https://doi.org/10.1109/ISQED57927.2023.10129353

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Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine

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book article

DeepVigor: VulnerabIlity Value RanGes and FactORs for DNNs’ Reliability AssessmentAhmadilivani, Mohammad Hasan; Taheri, Mahdi; Raik, Jaan; Daneshtalab, Masoud; Jenihhin, MaksimIEEE European Test Symposium (ETS) : Venice, Italy, 22-26 May 2023 : proceedings2023 / 6 p. : ill https://doi.org/10.1109/ETS56758.2023.10174133

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Enhancing fault resilience of QNNs by selective neuron splittingAhmadilivani, Mohammad Hasan; Taheri, Mahdi; Raik, Jaan; Daneshtalab, Masoud; Jenihhin, Maksim2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)2023 / 5 p. : ill https://doi.org/10.1109/AICAS57966.2023.10168633

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Exploration of Activation Fault Reliability in Quantized Systolic Array-Based DNN AcceleratorsTaheri, Mahdi; Cherezova, Natalia; Ansari, Mohammad Saeed; Jenihhin, Maksim; Mahani, Ali; Daneshtalab, Masoud; Raik, Jaan25th International Symposium on Quality Electronic Design (ISQED)2025 / 8 p. : ill https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10528372

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Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine

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journal article

A fault-resistant architecture for AES S-box architectureTaheri, Mahdi; Sheikhpour, Saeideh; Ansari, Mohammad Saeed; Mahani, AliJournal of Applied Research in Electrical Engineering2021 / p. 86-92 https://doi.org/10.22055/jaree.2021.36230.1020

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FORTUNE: A Negative Memory Overhead Hardware-Agnostic Fault TOleRance TechniqUe in DNNsNazari, Samira; Taheri, Mahdi; Azarpeyvand, Ali; Afsharchi, Mohsen; Ghasempouri, Tara; Herglotz, Christian; Daneshtalab, Masoud; Jenihhin, Maksim2024 IEEE 33rd Asian Test Symposium (ATS)2024 / p. 1-6 : ill https://doi.org//10.1109/ATS64447.2024.10915463

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Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine

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Heterogeneous Approximation of DNN HW Accelerators based on Channels VulnerabilityCherezova, Natalia; Pappalardo, Salvatore; Taheri, Mahdi; Ahmadilivani, Mohammad Hasan; Deveautour, Bastien; Bosio, Alberto; Raik, Jaan; Jenihhin, Maksim2024 IFIP/IEEE 32nd International Conference on Very Large Scale Integration (VLSI-SoC)2024 / 4 p. : ill https://doi.org//10.1109/VLSI-SoC62099.2024.10767798

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Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine

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journal article

A high-performance MEMRISTOR-based Smith-Waterman DNA sequence alignment using FPNI structureTaheri, Mahdi; Zandevakili, Hamed; Mahani, AliJournal of Applied Research in Electrical Engineering2021 / p. 59-68 https://doi.org/10.22055/jaree.2021.36117.1016

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Keynote: cost-efficient reliability for Edge-AI chipsJenihhin, Maksim; Taheri, Mahdi; Cherezova, Natalia; Ahmadilivani, Mohammad Hasan; Selg, Hardi; Jutman, Artur; Shibin, Konstantin; Tsertov, Anton; Devadze, Sergei; Kodamanchili, Rama Mounika; Rafiq, Ahsan; Raik, Jaan; Daneshtalab, Masoud2024 IEEE 25th Latin American Test Symposium (LATS)2024 / 2 p https://doi.org/10.1109/LATS62223.2024.10534610 Article at Scopus

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Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine

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dissertation

Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamineTaheri, Mahdi2025 https://www.ester.ee/record=b5728368*est https://digikogu.taltech.ee/et/Item/9cf79768-17bc-44ec-a828-e4ccf6cf93f1 https://doi.org/10.23658/taltech.4/2025

dissertation

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A novel fault-tolerant logic style with self-checking capabilityTaheri, Mahdi; Sheikhpour, Saeideh; Mahani, Ali; Jenihhin, MaksimProceedings - 2022 IEEE 28th International Symposium on On-Line Testing and Robust System Design, IOLTS 20222022 / art. 183305 : ill https://doi.org/10.1109/IOLTS56730.2022.9897818

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SAFFIRA: a Framework for Assessing the Reliability of Systolic-Array-Based DNN AcceleratorsTaheri, Mahdi; Daneshtalab, Masoud; Raik, Jaan; Jenihhin, Maksim; Pappalardo, Salvatore; Jimenez, Paul; Deveautour, Bastien; Bosio, Alberto2024 27th International Symposium on Design & Diagnostics of Electronic Circuits & Systems (DDECS) : 03-05 April 2024, Kielce, Poland2024 / p. 19–24 : ill https://doi.org//10.1109/DDECS60919.2024.10508925

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Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine

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book article EST / book article ENG

Special session : approximation and fault resiliency of DNN acceleratorsAhmadilivani, Mohammad Hasan; Barbareschi, Mario; Barone, Salvatore; Bosio, Alberto; Daneshtalab, Masoud; Torca, Salvatore Della; Gavarini, Gabriele; Jenihhin, Maksim; Raik, Jaan; Taheri, Mahdi2023 IEEE 41st VLSI Test Symposium (VTS) : proceedings2023 / 10 p. : ill https://doi.org/10.1109/VTS56346.2023.10140043 Conference proceeding at Scopus Article at Scopus Article at WOS

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Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine

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Special session: reliability assessment recipes for DNN acceleratorsAhmadilivani, Mohammad Hasan; Bosio, Alberto; Deveautour, Bastien; Dos Santos, Fernando Fernandes; Guerrero-Balaguera, Juan-David; Jenihhin, Maksim; Kritikakou, Angeliki; Sierra, Robert Limas; Raik, Jaan; Taheri, Mahdi42nd IEEE VLSI Test Symposium, VTS 20242024 / 11 p. : ill https://doi.org/10.1109/VTS60656.2024.10538707 Conference proceedings at Scopus Article at Scopus Article at WOS

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Methods for reliability assessment and enhancement of deep neural networks hardware accelerators = Süvanärvivõrkude riistvara kiirendite töökindluse hindamine ja täiustamine

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A systematic literature review on hardware reliability assessment methods for deep neural networksAhmadilivani, Mohammad Hasan; Taheri, Mahdi; Raik, Jaan; Daneshtalab, Masoud; Jenihhin, MaksimACM Computing Surveys2024 / art. 141, 39 p. : ill https://doi.org/10.1145/3638242 Journal metrics at Scopus Article at Scopus Journal metrics at WOS Article at WOS

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Taheri, Mahdi (author)

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