TY - GEN
T1 - Emerging Computing Devices
T2 - 26th IEEE European Test Symposium, ETS 2021
AU - Bosio, Alberto
AU - O'Connor, Ian
AU - Traiola, Marcello
AU - Echavarria, Jorge
AU - Teich, Jurgen
AU - Hanif, Muhammad Abdullah
AU - Shafique, Muhammad
AU - Hamdioui, Said
AU - Deveautour, Bastien
AU - Girard, Patrick
AU - Virazel, Arnaud
AU - Bertels, Koen
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/5/24
Y1 - 2021/5/24
N2 - The paper addresses some of the opportunities and challenges related to test and reliability of three major emerging computing paradigms; i.e., Quantum Computing, Computing engines based on Deep Neural Networks for AI, and Approximate Computing (AxC). We present a quantum accelerator showing that it can be done even without the presence of very good qubits. Then, we present Dependability for Artificial Intelligence (AI) oriented Hardware. Indeed, AI applications shown relevant resilience properties to faults, meaning that the testing strongly depends on the application behavior rather than on the hardware structure. We will cover AI hardware design issues due to manufacturing defects, aging faults, and soft errors. Finally, We present the use of AxC to reduce the cost of hardening a digital circuit without impacting its reliability. In other words how to go beyond usual modular redundancy scheme.
AB - The paper addresses some of the opportunities and challenges related to test and reliability of three major emerging computing paradigms; i.e., Quantum Computing, Computing engines based on Deep Neural Networks for AI, and Approximate Computing (AxC). We present a quantum accelerator showing that it can be done even without the presence of very good qubits. Then, we present Dependability for Artificial Intelligence (AI) oriented Hardware. Indeed, AI applications shown relevant resilience properties to faults, meaning that the testing strongly depends on the application behavior rather than on the hardware structure. We will cover AI hardware design issues due to manufacturing defects, aging faults, and soft errors. Finally, We present the use of AxC to reduce the cost of hardening a digital circuit without impacting its reliability. In other words how to go beyond usual modular redundancy scheme.
KW - AI hardware
KW - Approximate Computing
KW - Emerging Computing Paradigm
KW - Quantum Computing
KW - Reliability
KW - Testing
UR - http://www.scopus.com/inward/record.url?scp=85111018492&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85111018492&partnerID=8YFLogxK
U2 - 10.1109/ETS50041.2021.9465409
DO - 10.1109/ETS50041.2021.9465409
M3 - Conference contribution
AN - SCOPUS:85111018492
T3 - Proceedings of the European Test Workshop
BT - Proceedings - 2021 IEEE European Test Symposium, ETS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 24 May 2021 through 28 May 2021
ER -