Marco Rios

Orcid: 0000-0001-8251-6390

According to our database1, Marco Rios authored at least 13 papers between 2019 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Overflow-free Compute Memories for Edge AI Acceleration.
ACM Trans. Embed. Comput. Syst., October, 2023

Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference.
IEEE Trans. Emerg. Top. Comput., 2023

A 16-bit Floating-Point Near-SRAM Architecture for Low-power Sparse Matrix-Vector Multiplication.
Proceedings of the 31st IFIP/IEEE International Conference on Very Large Scale Integration, 2023

2022
A Hardware/Software Co-Design Vision for Deep Learning at the Edge.
IEEE Micro, 2022

Error Resilient In-Memory Computing Architecture for CNN Inference on the Edge.
Proceedings of the GLSVLSI '22: Great Lakes Symposium on VLSI 2022, Irvine CA USA, June 6, 2022

2021
A Flexible In-Memory Computing Architecture for Heterogeneously Quantized CNNs.
Proceedings of the IEEE Computer Society Annual Symposium on VLSI, 2021

Running Efficiently CNNs on the Edge Thanks to Hybrid SRAM-RRAM In-Memory Computing.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

2020
BLADE: An in-Cache Computing Architecture for Edge Devices.
IEEE Trans. Computers, 2020

Write Termination Circuits for RRAM: A Holistic Approach From Technology to Application Considerations.
IEEE Access, 2020

Exploration Methodology for BTI-Induced Failures on RRAM-Based Edge AI Systems.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

RRAM-VAC: A Variability-Aware Controller for RRAM-based Memory Architectures.
Proceedings of the 25th Asia and South Pacific Design Automation Conference, 2020

2019
An Associativity-Agnostic in-Cache Computing Architecture Optimized for Multiplication.
Proceedings of the 27th IFIP/IEEE International Conference on Very Large Scale Integration, 2019

Functionality Enhanced Memories for Edge-AI Embedded Systems.
Proceedings of the 19th Non-Volatile Memory Technology Symposium, 2019


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