RESOURCE-EFFICIENT SENSING THROUGH DYNAMIC ATTENTION-SCALABILITY

Project Information

Re-SENSE

Grant agreement ID: 715037

DOI

10.3030/715037

Project closed

EC signature date 12 October 2016

Start date 1 March 2017

End date 28 February 2022

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 484 562,00

EU contribution

€ 1 484 562,00

Coordinated by

KATHOLIEKE UNIVERSITEIT LEUVEN
Belgium

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Peer reviewed articles (8)

Optimized Hierarchical Cascaded Processing

Author(s): Koen Goetschalckx, Bert Moons, Steven Lauwereins, Martin Andraud, Marian Verhelst
Published in: IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Issue 8/4, 2018, Page(s) 884-894, ISSN 2156-3357
Publisher: IEEE Circuits and Systems Society
DOI: 10.1109/jetcas.2018.2839347

Vocell: A 65-nm Speech-Triggered Wake-Up SoC for 10-$\mu$ W Keyword Spotting and Speaker Verification

Author(s): Juan Sebastian P. Giraldo, Steven Lauwereins, Komail Badami, Marian Verhelst
Published in: IEEE Journal of Solid-State Circuits, Issue 55/4, 2020, Page(s) 868-878, ISSN 0018-9200
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/jssc.2020.2968800

GRAPHOPT: constrained-optimization-based parallelization of irregular graph

Author(s): Nimish Shah, Wannes Meert, and Marian Verhelst
Published in: IEEE Transactions on Parallel and Distributed Systems, 2022, ISSN 1045-9219
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tpds.2022.3151194

Architecture optimization for energy-efficient resolution-scalable 8–12-bit SAR ADCs

Author(s): Thomas Bos, Komail Badami, Wim Dehaene, Marian Verhelst
Published in: Analog Integrated Circuits and Signal Processing, Issue 97/3, 2018, Page(s) 437-448, ISSN 0925-1030
Publisher: Kluwer Academic Publishers
DOI: 10.1007/s10470-018-1235-0

Embedded Deep Neural Network Processing: Algorithmic and Processor Techniques Bring Deep Learning to IoT and Edge Devices

Author(s): Marian Verhelst, Bert Moons
Published in: IEEE Solid-State Circuits Magazine, Issue 9/4, 2017, Page(s) 55-65, ISSN 1943-0582
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/mssc.2017.2745818

High-Utilization, High-Flexibility Depth-First CNN Coprocessor for Image Pixel Processing on FPGA

Author(s): Steven Colleman, Marian Verhelst
Published in: IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Issue 29/3, 2021, Page(s) 461-471, ISSN 1063-8210
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tvlsi.2020.3046125

On the Convexity of Bit Depth Allocation for Linear MMSE Estimation in Wireless Sensor Networks

Author(s): Fernando de la Hucha Arce, Panagiotis Patrinos, Marian Verhelst, Alexander Bertrand
Published in: IEEE Signal Processing Letters, Issue 27, 2020, Page(s) 291-295, ISSN 1070-9908
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/lsp.2020.2967592

Dynamic Sensor-Frontend Tuning for Resource Efficient Embedded Classification

Author(s): Laura Galindez, Komail Badami, Jonas Vlasselaer, Wannes Meert, Marian Verhelst
Published in: IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Issue 8/4, 2018, Page(s) 858-872, ISSN 2156-3357
Publisher: IEEE Circuits and Systems Society
DOI: 10.1109/jetcas.2018.2850451

Conference proceedings (8)

Acceleration of probabilistic reasoning through custom processor architecture

Author(s): Nimish Shah, Laura I. Galindez Olascoaga, Wannes Meert, Marian Verhelst
Published in: 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2020, Page(s) 322-325, ISBN 978-3-9819263-4-7
Publisher: IEEE
DOI: 10.23919/date48585.2020.9116326

Discrete samplers for approximate inference in probabilistic machine learning

Author(s): Shirui Zhao, Nimish Shah, Wannes Meert, and Marian Verhelst
Published in: 2022
Publisher: IEEE

Exploiting system configurability towards dynamic accuracy-power trade-offs in sensor front-ends

Author(s): O. Laura I. Galindez, Komail Badami, V. Rajesh Pamula, Steven Lauwereins, Wannes Meert, Marian Verhelst
Published in: 2016 50th Asilomar Conference on Signals, Systems and Computers, 2016, Page(s) 1027-1031, ISBN 978-1-5386-3954-2
Publisher: IEEE
DOI: 10.1109/acssc.2016.7869524

Towards Hardware-Aware Tractable Learning of Probabilistic Models

Author(s): Laura I. Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst, Guy Van den Broeck
Published in: Accepted for Publication at Proceedings of the Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019)., 2019
Publisher: NeurIPS

ProbLP: A framework for low-precision probabilistic inference

Author(s): Nimish Shah ; Laura I. Galindez Olascoaga ; Wannes Meert ; Marian Verhelst
Published in: DAC '19 Proceedings of the 56th Annual Design Automation Conference 2019, 2019
Publisher: DAC
DOI: 10.1145/3316781.3317885

Mixed-signal programmable non-linear interface for resource-efficient multi-sensor analytics

Author(s): Komail Badami, Juan-Carlos Pena Ramos, Steven Lauwereins, Marian Verhelst
Published in: 2018 IEEE International Solid - State Circuits Conference - (ISSCC), 2018, Page(s) 344-346, ISBN 978-1-5090-4940-0
Publisher: IEEE
DOI: 10.1109/isscc.2018.8310325

Towards Hardware-Aware Tractable Learning of Probabilistic Models (workshop version)

Author(s): L Galindez Olascoaga, W. Meert, M. Verhelst, G. Van den Broeck
Published in: 3rd Tractable Probabilistic Modeling Workshop colocated with the 36th International Conference on Machine Learning (TPM-ICML 2019), 2019
Publisher: TPM-ICML 2019

On the use of Bayesian Networks for Resource-Efficient Self-Calibration of Analog/RF ICs

Author(s): Martin Andraud, Laura Galindez, Yichuan Lu, Yiorgos Makris, Marian Verhelst
Published in: 2018 IEEE International Test Conference (ITC), 2018, Page(s) 1-10, ISBN 978-1-5386-8382-8
Publisher: IEEE
DOI: 10.1109/test.2018.8624893

Book chapters (3)

Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams

Author(s): Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst
Published in: Advances in Intelligent Data Analysis XVIII - 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29, 2020, Proceedings, Issue 12080, 2020, Page(s) 184-196, ISBN 978-3-030-44583-6
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-44584-3_15

Dynamic Complexity Tuning for Hardware-Aware Probabilistic Circuits

Author(s): Laura I. Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst
Published in: IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning - Second International Workshop, IoT Streams 2020, and First International Workshop, ITEM 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14-18, 2020, Revised Selected Papers, Issue 1325, 2020, Page(s) 283-295, ISBN 978-3-030-66769-6
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-66770-2_21

Towards Resource-Efficient Classifiers for Always-On Monitoring

Author(s): Jonas Vlasselaer, Wannes Meert, Marian Verhelst
Published in: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10–14, 2018, Proceedings, Part III, Issue 11053, 2019, Page(s) 305-321, ISBN 978-3-030-10996-7
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-10997-4_19

Other (1)

PRU: Probabilistic Reasoning processing Unit for resource-efficient AI

Author(s): Nimish Shah, Laura I. Galindez Olascoaga, Wannes Meert and Marian Verhelst
Published in: HotChips, 2019
Publisher: HotChips