University Scholarship
Publications and Grants

Subject: Edge computing

FAST ID: 2020291 | WorldCat Record

Academic Publications

Overflow-free Compute Memories for Edge AI Acceleration
Flavio Ponzina; Marco Rios; Alexandre Levisse; Giovanni Ansaloni; David Atienza
Acm Transactions on Embedded Computing Systems, 2023, journal article
Cited by 8
Electrical and Computer Engineering GREW Fellow
Artificial intelligence Edge computing Machine learning Microprocessors
A Hardware/Software Co-Design Vision for Deep Learning at the Edge
Flavio Ponzina; et al.
IEEE Micro, 2022, journal article
Cited by 16
Electrical and Computer Engineering GREW Fellow
Computer hardware description languages Deep learning (Machine learning) Edge computing Machine learning
E2CNNs: Ensembles of Convolutional Neural Networks to Improve Robustness Against Memory Errors in Edge-Computing Devices
Flavio Ponzina; Miguel Peon-Quiros; Andreas Burg; David Atienza
IEEE Transactions on Computers, 2021, journal article
Cited by 23
Electrical and Computer Engineering GREW Fellow
Edge computing Ensemble learning (Machine learning) Robust control
Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices
Benoit W. Denkinger; Flavio Ponzina; et al.
IEEE Design & Test, 2020, journal article Cited by 14
Electrical and Computer Engineering GREW Fellow
Deep learning (Machine learning) Edge computing Energy consumption Resilience (Personality trait)
Multimedia Sensing as a Service (MSaaS): Exploring Resource Saving Potentials of at Cloud-Edge IoTs and Fogs
Wei Wang; Qin Wang; Kazem Sohraby
IEEE Internet of Things Journal, 2016, journal article
Cited by 55
Computer Science GREW Fellow
Cloud computing Edge computing Energy consumption Internet of things

Conference Presentations

E-QUARTIC: Energy Efficient Edge Ensemble of Convolutional Neural Networks for Resource-Optimized Learning
Le Zhang; Onat Gungor; Flavio Ponzina; Tajana Rosing
Artificial intelligence Edge computing Machine learning Neural networks (Computer science)
Error Resilient In-Memory Computing Architecture for CNN Inference on the Edge
Marco Rios; Flavio Ponzina; Giovanni Ansaloni; Alexandre Levisse; David Atienza
Proceedings of the Great Lakes Symposium on Vlsi 2022, 2022, conference paper
Electrical and Computer Engineering GREW Fellow
Artificial intelligence Deep learning (Machine learning) Edge computing Machine learning
Running Efficiently CNNs on the Edge Thanks to Hybrid SRAM-RRAM In-Memory Computing
Marco Rios; Flavio Ponzina; Giovanni Ansaloni; Alexandre Levisse; David Atienza
2021 Design, Automation & Test in Europe Conference & Exhibition (Date), 2021, conference paper
Electrical and Computer Engineering GREW Fellow
Artificial intelligence Edge computing Machine learning Neural networks (Computer science)