Technology and hardware for neuromorphic computing

A Synergistic Approach of Interfacial Layer Engineering and READ-Voltage Optimisation in HfO 2 Based FeFETs for In- Memory-Computing Applications

Autori: Yannick Raffel, Sourav De, Maximilian Lederer, Ricardo Revello Olivo, Raik Hoffmann, Sunanda Thunder, Luca Pirro, Sven Beyer, Talha Chohan, Thomas Kämpfe, Konrad Seidel, Johannes Heitmann
Pubblicato in: ACS Applied Electronic Materials, Numero 00000000, 2022, ISSN 0000-0000
Editore: ACS
DOI: 10.1021/acsaelm.2c00771

Demonstration of Multiply-Accumulate Operation with 28 nm FeFET Crossbar Array

Autori: S. De, F. Müller, N. Laleni, M. Lederer, Y. Raffel, S. Mojumder, S. Abdulazhanov, T. Ali, S. Dünkel, S. Beyer, K. Seidel, T. Kämpfe
Pubblicato in: IEEE Electron Device Letters, Numero 00000000, 2022, ISSN 0000-0000
Editore: IEEE
DOI: 10.1109/led.2022.3216558

Ultra-Low-Power FDSOI Neural Circuits for Extreme-Edge Neuromorphic Intelligence

Autori: Rubino, Arianna; Livanelioglu, Can; Qiao, Ning; Payvand, Melika; Indiveri, Giacomo
Pubblicato in: IEEE Transactions on Circuits and Systems I: Regular Papers, 68, Numero 15498328, 2021, ISSN 1549-8328
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tcsi.2020.3035575

Optimizing the Energy Consumption of Spiking Neural Networks for Neuromorphic Applications.

Autori: Martino Sorbaro; Martino Sorbaro; Qian Liu; Massimo Bortone; Sadique Sheik
Pubblicato in: Frontiers in Neuroscience, Vol 14 (2020), Numero 00000000, 2020, ISSN 0000-0000
Editore: Frontiers in Neuroscience
DOI: 10.48550/arxiv.1912.01268

READ-Optimized 28nm HKMG Multi-bit FeFET Synapses for Inference-Engine Applications

Autori: S. De, F. Müller, H.-H. Le, M. Lederer, Y. Raffel, T. Ali, D. Lu, T. Kämpfe
Pubblicato in: IEEE Journal of the Electron Device Society, Numero 21686734, 2022, ISSN 2168-6734
Editore: Institute of Electrical and Electronics Engineers Inc.
DOI: 10.1109/jeds.2022.3195119

Optimizing Ferroelectric and Interface Layers in HZO-Based FTJs for Neuromorphic Applications

Autori: A. Sünbül, T. Ali, K. Mertens, R. Olivo, D. Lehninger, F. Müller, M. Lederer, K. Kühnel, M. Rudolph, S. Oehler, R. Hoffmann, K. Zimmermann, K. Biedermann, P. Schramm, M. Czernohorsky, K. Seidel, T. Kämpfe, L. M. Eng
Pubblicato in: IEEE Transactions on Electron Devices, Numero 00189383, 2021, ISSN 0018-9383
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/ted.2021.3131971

FeFET Multi-Bit Content-Addressable Memories for In-Memory Nearest Neighbor Search

Autori: A. Kazemi, M.M. Sharifi, A.F. Balon Laguna, F. Muller, X. Yin, T. Kampfe, M. Niemier, X.S. Hu
Pubblicato in: IEEE Transactions on Computers, Numero 00189340, 2021, ISSN 0018-9340
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tc.2021.3136576

Power-Efficient Gesture Sensing for Edge Devices: A 60 GHz Radar using Spiking Neural Networks

Autori: M. Arsalan, A. Santra, V. Issakov
Pubblicato in: IEEE Sensors Journal, 2022, ISSN 0000-0000
Editore: IEEE

Achieving software-equivalent accuracy for hyperdimensional computing with ferroelectric-based in-memory computing

Autori: Arman Kazemi, Franz Müller, Mohammad Mehdi Sharifi, Hamza Errahmouni, Gerald Gerlach, Thomas Kämpfe, Mohsen Imani, X. Sharon Hu, Michael Niemier
Pubblicato in: Scientific Reports, 2022, ISSN 0000-0000
Editore: Nature Springer

Power-Efficient Gesture Sensing for Edge Devices: Mimicking Fourier Transforms with Spiking Neural Networks

Autori: M. Arsalan, A. Santra, V. Issakov
Pubblicato in: Applied Intelligence, 2022, ISSN 0000-0000
Editore: Springer

Analysis of Edge-Optimized Deep Learning classifiers for radar-based gesture recognition

Autori: M. Chmurski, M. Zubert; K. Bierzynski, A. Santra
Pubblicato in: IEEE Access, Numero 00000000, 2021, ISSN 0000-0000
Editore: IEEE
DOI: 10.1109/access.2021.3081353

SPICE compatible semi-empirical compact model for ferroelectric hysteresis

Autori: M. Lederer, R. Olivo, N. Yadav, S. De, K. Seidel, L. M. Eng, T. Kämpfe
Pubblicato in: Solid State Electronics, Numero 00000000, 2023, ISSN 0000-0000
Editore: Elsevier
DOI: 10.1016/j.sse.2022.108501

2022 Roadmap on Neuromorphic Computing and Engineering

Autori: "Christensen, Dennis Valbjø rn; Dittmann, Regina; Linares-Barranco, Bernabe; Sebastian, Abu; Le Gallo, Manuel; Redaelli, Andrea; Slesazeck, Stefan; Mikolajick, Thomas; Spiga, Sabina; Menzel, Stephan; Valov, Ilia; Milano, Gianluca; Ricciardi, Carlo; Liang, Shi-Jun; Miao, Feng; Lanza, Mario; Quill, Tyler J.; Keene, Scott Tom; Salleo, Alberto; Grollier, Julie; Markovic, Danijela; Mizrahi, Alice;"
Pubblicato in: Neuromorphic Computing and Engineering, Numero 00000000, 2022, ISSN 0000-0000
Editore: IOP Publishing
DOI: 10.17863/cam.85140

Ferroelectric field effect transistors as a synapse for neuromorphic application

Autori: M. Lederer, T. Kämpfe, T. Ali, F. Müller, R. Olivo, R. Hoffmann, N. Laleni, K. Seidel
Pubblicato in: IEEE Transactions on Electron Devices, Numero 00189383, 2021, ISSN 0018-9383
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/ted.2021.3068716

Highly-Optimized Radar-Based Gesture Recognition System with Depthwise Expansion Module.

Autori: Mateusz Chmurski; Gianfranco Mauro; Avik Santra; Mariusz Zubert; Gökberk Dagasan
Pubblicato in: MDPI Sensors, Numero 00000000, 2021, ISSN 0000-0000
Editore: MDPI
DOI: 10.3390/s21217298

Effect of Al2O3 interlayers on the microstructure and electrical response of ferroelectric doped HfO 2 thin films

Autori: Maximilian Lederer, Konrad Seidel, Ricardo Olivo, Thomas Kämpfe, Lukas M. Eng
Pubblicato in: Frontiers in Nanotechnology, Numero 00000000, 2022, ISSN 0000-0000
Editore: Frontiers
DOI: 10.3389/fnano.2022.900379

Increasing Throughput of In-Memory DNN Accelerators by Flexible Layer-wise DNN Approximation

Autori: C. De la Parra, T. Soliman, A. Guntoro, A. Kumar, N. Wehn
Pubblicato in: IEEE Micro, Numero 00000000, 2022, ISSN 0000-0000
Editore: IEEE
DOI: 10.1109/mm.2022.3196865

First Demonstration of Ultra-High Precision 4Kb 28nm HKMG 1FeFET-1T Based

Autori: S. De, F. Müller, N. Laleni, T. Soliman, A. Shrivastava, N. Yadav, S. Abdulazhanov, M. Lederer, S. Mojumder, A. Vardar, T. Ali, T. Kirchner, F.-X. Liang, H.-H. Le, Md.A. Baig, D. Lu, K. Seidel, T. Kämpfe
Pubblicato in: TechRxiv, Numero 00000000, 2022, ISSN 0000-0000
Editore: IEEE
DOI: 10.36227/techrxiv.19491212.v1

FELIX: A Ferroelectric FET Based Low Power Mixed-Signal In-Memory Architecture for DNN Acceleration

Autori: T. Soliman, N. Laleni, T. Kirchner, F. Müller, A. Shrivastava, T. Kämpfe, A. Guntoro, N. Wehn
Pubblicato in: ACM Transactions on Embedded Computing Systems, Numero 00000000, 2022, ISSN 0000-0000
Editore: ACM
DOI: 10.1145/3529760

Spiking Neural Network-Based Radar Gesture Recognition System Using Raw ADC Data

Autori: M. Arsalan, A. Santra, V. Issakov
Pubblicato in: IEEE Sensor Letters, Numero 00000000, 2022, ISSN 0000-0000
Editore: IEEE
DOI: 10.1109/lsens.2022.3173589

RadarSNN: A Resource Efficient Gesture Sensing System Based on mm-Wave Radar

Autori: M. Arsalan, A. Santra, V. Issakov
Pubblicato in: IEEE Transactions on Microwave Theory and Techniques, Numero 00000000, 2022, ISSN 0000-0000
Editore: IEEE
DOI: 10.1109/tmtt.2022.3148403

Enabling technologies for the future heterogeneous neuromorphic accelerators

Autori: Elisa Vianello, Alexandre Valentian
Pubblicato in: Journal Neuromorphic Computing and Engineering, Numero 00000000, 2022, ISSN 0000-0000
Editore: IOP Publishing
DOI: 10.1088/2634-4386/ac4a83

Real-time ultra-low power ECG anomaly detection using an event-driven neuromorphic processor

Autori: Felix Christian Bauer; Dylan R. Muir; Giacomo Indiveri
Pubblicato in: IEEE Transactions on Biomedical Circuits and Systems, Numero 19324545, 2019, ISSN 1932-4545
Editore: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tbcas.2019.2953001

Supervised training of spiking neural networks for robust deployment on mixed-signal neuromorphic processors.

Autori: Julian Büchel; Dmitrii Zendrikov; Sergio Solinas; Giacomo Indiveri; Dylan R. Muir
Pubblicato in: Scientific Reports, Vol 11, Iss 1, Numero 00000000, 2021, ISSN 0000-0000
Editore: Nature
DOI: 10.1038/s41598-021-02779-x

The SpiNNaker 2 Processing Element Architecture for Hybrid Digital Neuromorphic Computing

Autori: S. Hoppner, Y. Yan, B. Vogginger, C. Liu, F. Kelber, A. Dixius, S. Scholze, J. Partzsch, M. Stolba, F. Neumarker, G. Ellguth, S. Hartmann, S. Schiefer, T.Hocker, D. Walter, G. Liu, M. Mikaitis, J. Garside, S. Furber, C. Mayr
Pubblicato in: arxiv, Numero 00000000, 2022, ISSN 0000-0000
Editore: arxiv
DOI: 10.48550/arxiv.2103.08392

Feasibility of Wafer Exchange for European Edge AI Pilot Lines

Autori: A.F. Wandesleben, D. Truffier-Boutry, V. Brackmann, B. Lilienthal-Uhlig, M. Jaysnkar, S. Beckx, I. Madarevic, A. Demarest, B. Hintze, F. Hochschulz, Y. Le Tiec, A. Spessot, F. Nemouchi
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022
Editore: River Publishers

Emerging In-memory Computing for Neural Networks

Autori: Nelli Laleni, Taha Soliman, Alptekin Vardar, Thomas Kämpfe
Pubblicato in: Embedded Artificial Intelligence, 2022
Editore: River Publishers

Using FeFETs as Resistive Synapses in Crossbar-based Analog MAC Accelerating Units

Autori: L. Zhang, D. Borggreve, F. Vanselow, R. Brederlow
Pubblicato in: Intelligent Edge-Embedded Technologies for Digitising Industry, 2022
Editore: River Publishers

Food Ingredients Recognition Through Multi-label Learning

Autori: Rameez Ismail
Pubblicato in: Embedded Artificial Intelligence, 2022
Editore: River Publishers

Emerging In-memory Computing for Neural Networks

Autori: N. Laleni, T. Soliman, A. Vardar, T. Kämpfe
Pubblicato in: Intelligent Edge-Embedded Technologies for Digitising Industry, 2022
Editore: River Publishers

Sub-mW Neuromorphic SNN audio processing applications with Rockpool and Xylo

Autori: Hannah Bos, Dylan Muir
Pubblicato in: Embedded Artificial Intelligence, 2022
Editore: River Publishers

Temporal Delta Layer: Exploiting Temporal Sparsity in Deep Neural Networks for Time-Series Data

Autori: P. Vijayan, A. Yousefzadeh, M. Sifalakis, R. van Leuken
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022
Editore: River Publishers

Low-Power Analog In-memory Computing Neuromorphic Circuits

Autori: Roland Müller
Pubblicato in: Embedded Artificial Intelligence, 2022
Editore: River Publishers

Benchmarking the Epiphany Processor as a Reference Neuromorphic Architecture

Autori: M. Molendijk, K. Vadivel, F. Corradi, G.-J. van Schaik, A. Yousefzadeh, H. Corporaal
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022
Editore: River Publishers

An Embedding Workflow for Tiny Neural Networks on ARM Cortex-M0(+) Cores

Autori: Jianyu Zhao
Pubblicato in: Embedded Artificial Intelligence, 2022
Editore: River Publishers

Technology and Hardware for Neuromorphic Computing

Autori: Björn Debaillie, Ilja Ocket, and Peter Debacker
Pubblicato in: Intelligent Edge-Embedded Technologies for Digitising Industry, 2022
Editore: River Publishers
DOI: 10.13052/rp-9788770226103

Exploiting resiliency for Kernel-wise CNN approximation enabled by adaptive hardware Design

Autori: C. De la Parra, A. El-Yamany, T. Soliman, A. Kumar, N. Wehn, A. Guntoro,
Pubblicato in: IEEE International Symposium on Circuits and Systems (ISCAS), 2021
Editore: IEEE
DOI: 10.1109/iscas51556.2021.9401517

A Novel DRAM-Based Process-in-Memory Architecture and its Implementation for CNNs

Autori: Chirag Sudarshan; Taha Soliman; Cecilia De la Parra; Christian Weis; Leonardo Ecco; Matthias Jung; Norbert Wehn; Andre Guntoro
Pubblicato in: Asia and South Pacific Design Automation Conference (ASP-DAC), 2021
Editore: IEEE
DOI: 10.1145/3394885.3431522

Interfacial Layer Engineering to Enhance Endurance and Noise Immunity of FeFETs for IMC Applications

Autori: Y. Raffel, S. Thunder, M. Lederer, R. Olivo, R. Hoffmann, L. Pirro, S. Beyer, T. Chohan, P.T. Huang, S. De, T. Kämpfe, K. Seidel, J. Heitman
Pubblicato in: International Conference on IC Design and Technology (ICICDT), 2022
Editore: IEEE
DOI: 10.1109/icicdt56182.2022.993311

Tuneable linearity in HfO2 based multilevel FeFETs for neuromorphic computing

Autori: M. Lederer, T. Kämpfe, T. Ali, K. Seidel
Pubblicato in: European Materials Research Society (E-MRS), 2019
Editore: European Materials Research Society

ReckOn: A 28nm Sub-mm2 Task-Agnostic Spiking Recurrent Neural Network Processor Enabling On-Chip Learning over Second-Long Timescales

Autori: C. Frenkel, G. Indiveri
Pubblicato in: International Solid-State Circuits Conference (ISSCC), 2022
Editore: IEEE
DOI: 10.1109/isscc42614.2022.9731734

Efficient FeFET crossbar accelerator for binary neural networks

Autori: T. Soliman, R. Olivo, T. Kirchner, C. De La Parra, M. Lederer, T. Kämpfe, A. Guntoro, N. Wehn
Pubblicato in: International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2020
Editore: IEEE
DOI: 10.1109/asap49362.2020.00027

16kbit 1T1R OxRAM arrays embedded in 28nm FDSOI technology demonstrating low BER, high endurance, and compatibility with core logic transistors

Autori: L. Grenouillet, N. Castellani, A. Persico, V. Meli, S. Martin, O. Billoint, R. Segaud, S. Bernasconi, C. Pellissier, C. Jahan, C. Charpin-Nicolle, P. Dezest, C. Carabasse, P. Besombes, S. Ricavy, N.-P. Tran, A. Magalhaes-Lucas, A. Roman, C. Boixaderas, T. Magis, M. Bedjaoui, M. Tessaire, A. Seignard, F. Mazen, S. Landis, E. Vianello, G. Molas, F. Gaillard, J. Arcamone, E. Nowak
Pubblicato in: IEEE International Memory Workshop (IMW), 2021
Editore: IEEE
DOI: 10.1109/imw51353.2021.9439607

Integration of BEoL Compatible 1T1C FeFET Memory Into an Established CMOS Technology

Autori: D. Lehninger, H. Mähne, T. Ali, R. Hoffmann, R. Olivo, M. Lederer, K. Mertens, T. Kämpfe, K. Biedermann, M. Landwehr, A. Heinig, D. Wang, Y. Shen, K. Bernert, S. Thiem, K. Seidel
Pubblicato in: International Memory Workshop (IMW), 2022
Editore: IEEE
DOI: 10.1109/imw52921.2022.9779252

Microstructural implications for neuromorphic synapses based on ferroelectric hafnium oxide

Autori: F. Müller , M. Lederer, R. Olivo, A. Reck, T. Ali, K. Seidel, T. Kämpfe
Pubblicato in: IEEE International Symposium on Applications of Ferroelectrics (ISAF), 2021
Editore: IEEE
DOI: 10.1109/isaf51943.2021.9477384

LiMoSeg: Real-time Bird's Eye View based LiDAR Motion Segmentation

Autori: S. Mohapatra, M. Hodaei, S. Yogamani, S. Milz, H. Gotzig, M. Simon, H. Rashed, P. Maeder
Pubblicato in: International Conference on Computer Vision Theory and Applications (VISAPP), 2022
Editore: arxiv
DOI: 10.48550/arxiv.2111.04875

Efficient Hardware Approximation for Bit-Decomposition Based Deep Neural Network Accelerators

Autori: T. Soliman, A. Eldebiky, C. De La Parra, A. Guntoro, N. Wehn
Pubblicato in: International System-on-Chip Conference (SOCC), 2022
Editore: IEEE
DOI: 10.1109/socc56010.2022.9908072

Training for temporal sparsity in deep neural networks, application in video processing

Autori: A. Yousefzadeh, M. Sifalakis
Pubblicato in: International Joint Conference on Neural Networks (IJCNN), 2021
Editore: IEEE
DOI: 10.48550/arxiv.2107.07305

Crystallographic phase and orientation mapping of ferroelectric HfO2 thin films by transmission Kikuchi diffraction

Autori: M. Lederer, T. Kämpfe, C. Mart, T. Ali, L. Roy, K. Seidel
Pubblicato in: Dresden Nanoanalysis Symposium (DNS), 2019
Editore: Dresden Nanoanalysis Symposium

Event Camera Data Classification Using Spiking Networks with Spike-Timing-Dependent Plasticity

Autori: A. Safa, I. Ocket, A. Bourdoux, H. Sahli, Francky Catthoor, Georges G.E. Gielen
Pubblicato in: International Joint Conference on Neural Networks (IJCNN), 2022
Editore: IEEE
DOI: 10.1109/ijcnn55064.2022.9892362

In-Memory Nearest Neighbor Search with FeFET Multi-Bit Content-Addressable Memories

Autori: Arman Kazemi; Mohammad Mehdi Sharifi; Ann Franchesca Laguna; Franz Muller; Ramin Rajaei; Ricardo Olivo; Thomas Kampfe; Michael Niemier; X. Sharon Hu
Pubblicato in: Design, Automation & Test in Europe (DATE), 2021
Editore: IEEE
DOI: 10.48550/arxiv.2011.07095

In-Memory Computing exceeding 10000 TOPS/W using Ferroelectric Field Effect Transistors for EdgeAI Applications

Autori: N. Laleni, T. Soliman, F. Muller, S. Mojumder, T. Kirchner, M. Lederer, T. Hoffmann, A. Guntoro, N. Wehn, T. Kampfe
Pubblicato in: MikroSystemTechnik Congress (MSTK), 2021
Editore: IEEE

Ultra low power flexible precision FeFET based analog in-memory computing

Autori: T. Soliman, F. Müller, T. Kirchner, T. Hoffmann, H. Ganem, E. Karimov, T. Ali, M. Lederer, C. Sudarshan, T. Kämpfe, A. Guntoro, N. Wehn
Pubblicato in: IEEE International Electron Devices Meeting (IEDM), 2020
Editore: IEEE
DOI: 10.1109/iedm13553.2020.9372124

Semi-empirical and Verilog-A compatible compact model for ferroelectric hysteresis behavior

Autori: M. Lederer, O. R. Olivo, Y. Nandakishor, de Sourav, K. Seidel, E. Lukas, T. Kämpfe
Pubblicato in: International Conference on Simulation of Semiconductor Processes and Devices, 2022
Editore: IEEE

Memory Array Demonstration of fully integrated 1T-1C FeFET concept with separated ferroelectric MFM device in interconnect layer

Autori: K. Seidel, D. Lehninger, R. Hoffmann, T. Ali, M. Lederer, R. Revello, K. Mertens, K. Biedermann, Y. Shen, D. Wang, M. Landwehr, A. Heinig, T. Kämpfe, H. Mähne, K. Bernert, S. Thiem
Pubblicato in: VLSI Symposium on Technology & Circuits, 2022
Editore: IEEE
DOI: 10.1109/vlsitechnologyandcir46769.2022.9830141

A Ferroelectric FET based in-memory architecture for multi-precision neural networks

Autori: T. Soliman, R. Olivo, M. Lederer, T. Kämpfe, T. Kirchner, A. Guntoro, N. Wehn
Pubblicato in: IEEE International System-on-Chip Conference (SOCC), 2020
Editore: IEEE
DOI: 10.1109/socc49529.2020.9524750

Choosing the right combination of technology, design and tools is key for successful Edge AI solutions

Autori: Alexandre Valentian
Pubblicato in: AI Expo, 2020
Editore: ValleyML

Impact of the ferroelectric and interface layer optimization in a MFIS HZO based Ferroelectric Tunnel Junction for optimal neuromorphic based synaptic storage

Autori: T. Ali, A. Sünbül, K. Mertens, R. Revello, M. Lederer, D. Lehninger, F. Müller, K. Kühnel, M. Rudolph, S. Oehler, R. Hoffmann, K. Zimmermann, K. Biedermann, M. Czernohorsky, K. Seidel, T. Kämpfe, L.M. Eng
Pubblicato in: Silicon Nanoelectronics Workshop (SNW), 2021
Editore: IEEE
DOI: 10.1109/snw51795.2021.00032

Network insensitivity to parameter noise via adversarial regularization

Autori: Büchel, Julian; Faber, Fynn; Muir, Dylan R.
Pubblicato in: International Conference on Learning Representations (ICLR), 2022
Editore: ICLR
DOI: 10.48550/arxiv.2106.05009

Performance models and energy-optimal scheduling of DNNs on many-core hardware with dynamic power management

Autori: B. Vogginger, F. Kelber, S.B. Sampath, J. Partzsch, C. Mayr
Pubblicato in: Workshop on Compilers, Deployment, and Tooling for Edge AI (CDAI), 2022
Editore: IEEE

Quantization Considerations of Dense Layers in Convolutional Neural Networks for Resistive Crossbar Implementation

Autori: Lei Zhang; David Borggreve; Frank Vanselow; Ralf Brederlow
Pubblicato in: International Conference on Modern Circuits and Systems Technologies (MOCAST), 2020
Editore: IEEE
DOI: 10.1109/mocast49295.2020.9200280

Spectrum-based Single-Snapshot Super-Resolution Direction-of-Arrival Estimation using Deep Learning

Autori: M. Gall, M. Gardill, T. Horn, J. Fuchs
Pubblicato in: German Microwave Conference (GeMiC), 2020, ISBN 978-3-9820-3971-8
Editore: IEEE

Learning representations for neural networks applied to spectrum-based direction-of-arrival estimation for automotive radar

Autori: M. Gall, M. Gardill, J. Fuchs, T. Horn
Pubblicato in: MTT-S International Microwave Symposium (IMS), 2020
Editore: IEEE
DOI: 10.1109/ims30576.2020.9223841

Delta Activation Layer exploits temporal sparsity for efficient embedded video processing

Autori: Amirreza Yousefzadeh, Manolis Sifalakis
Pubblicato in: International Joint Conference on Neural Networks (IJCNN), 2022
Editore: IEEE
DOI: 10.1109/ijcnn55064.2022.9892578

Resource Efficient Gesture Sensing Based on FMCW Radar using Spiking Neural Networks

Autori: M. Arsalan,M. Chmurski, A. Santra, M. El-Masry, R. Weigel, V. Issakov
Pubblicato in: IEEE MTT-S International Microwave Symposium (IMS), 2021
Editore: IEEE
DOI: 10.1109/ims19712.2021.9574994

Contactless Low Power Air-Writing Based on FMCW Radar Networks Using Spiking Neural Networks

Autori: M. Arsalan, A. Santra, V. Issakov
Pubblicato in: IEEE International Conference on Machine Learning an Application (ICMLA), 2022
Editore: IEEE

FeFET versus DRAM based PIM Architectures: A Comparative Study

Autori: C. Sudarshan, T. Soliman, T. Kämpfe, C. Weis, N. Wehn
Pubblicato in: IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC), 2022
Editore: IEEE

Brain-inspired strategies for optimizing the design of neuromorphic sensory-processing systems

Autori: Giacomo Indiveri
Pubblicato in: IEEE International Electron Devices Meeting (IEDM), 2021
Editore: IEEE

Les approches hardware de l'IA économe en énergie

Autori: Alexandre Valentian
Pubblicato in: Planet Tech’Care, 2021
Editore: Planet Tech’Care

Continuously Learning to Detect People using Event Cameras: A Bio-inspired Visual System for Drones

Autori: A. Safa, I. Ocket, A. Bourdoux, H. Sahli, Francky Catthoor, Georges G.E. Gielen
Pubblicato in: International Conference on Intelligent Robots and Systems (IROS), 2022
Editore: IEEE
DOI: 10.48550/arxiv.2202.08023

Radar-Based Gesture Recognition System using Spiking Neural Network

Autori: M. Arsalan,M. Chmurski, A. Santra, M. El-Masry, G. Mauro, V. Issakov
Pubblicato in: IEEE International Conference on Emerging Technologies and Factory Automation, 2021
Editore: IEEE
DOI: 10.1109/etfa45728.2021.9613183

Influences on the nonlinearity of ferroelectric synapses for neuromorphic computing

Autori: M. Lederer, T. Kämpfe, T. Ali, Y. Gao, K. Seidel
Pubblicato in: International Symposium on Integrated Functionalities (ISIF), 2019
Editore: International Symposium on Integrated Functionalities

High-density 3D monolithically integrated multiple 1T1R multi-level-cell for neural networks

Autori: E. Esmanhotto, L. Brunet, N. Castellani, D. Bonnet, T. Dalgaty, L. Grenouillet, D.R.B Ly, C. Cagli, C. Vizioz, N. Allouti, F. Laulagnet, O. Gully, N. Bernard-Henriques, M. Bocquet, G. Molas, P. Vivet, D. Querlioz, J.M. Portal, S. Mitra, F. Andrieu, C. Fenouillet-Beranger, E. Nowak, E. Vianello
Pubblicato in: IEEE International Electron Devices Meeting (IEDM), 2020
Editore: IEEE
DOI: 10.1109/iedm13553.2020.9372019

Adaptable approximation based on bit decomposition for Deep Neural Network accelerators

Autori: T. Soliman, C. De La Parra, A. Guntoro and N. Wehn
Pubblicato in: International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2021
Editore: IEEE
DOI: 10.1109/aicas51828.2021.9458456

Exploiting FeFET Switching Stochasticity for Low-Power Reconfigurable Physical Unclonable Function

Autori: X. Guo, X. Ma, F. Müller, R. Olivo, J. Wu, K. Ni, T. Kämpfe, Y. Liu, H. Yang, X. Li
Pubblicato in: European Solid State Circuits Conference (ESSCIRC), 2021
Editore: IEEE
DOI: 10.1109/esscirc53450.2021.9567880

SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection for Autonomous Driving

Autori: S. Mohapatra, T. Mesquida, M. Hodaei, S. Yogamani, H. Gotzig, P. Maeder
Pubblicato in: International Conference on Event-Based Control, Communication, and Signal Processing (EBCCSP), 2022
Editore: IEEE
DOI: 10.1109/ebccsp56922.2022.9845647

Impact of Temperature on Reliability of MFIS HZO-based Ferroelectric Tunnel Junctions

Autori: A. Sünbül, T. Ali, Tarek, R. Hoffmann, R. Revello, Y. Raffel, P. Duhan, D. Lehninger, K. Kühnel, M. Rudolph, S. Oehler, P. Schramm, M. Czernohorsky, K. Seidel, T. Kämpfe, L.M. Eng
Pubblicato in: International Reliability Physics Symposium (IRPS), 2022
Editore: IEEE
DOI: 10.1109/irps48227.2022.9764585

28nm High-K-Metal Gate Ferroelectric Field Effect Transistors Based Artificial Synapses

Autori: S. De, Y. Raffel, S. Thunder, F. Müller, M. Lederer, T. Kämpfe
Pubblicato in: International Electron Devices & Materials Symposium (IEDMS), 2022
Editore: IEEE

Impact of parasitic wire resistance on accuracy and size of resistive crossbars

Autori: L. Zhang, D. Borggreve, F. Vanselow, R. Brederlow
Pubblicato in: IEEE International Symposium on Circuits and Systems (ISCAS), 2021
Editore: IEEE
DOI: 10.1109/iscas51556.2021.9401279

BEVDetNet: Bird's Eye View LiDAR Point Cloud based Real-time 3D Object Detection for Autonomous Driving

Autori: S. Mohapatra, S. Yogamani, H. Gotzig, S. Milz, P. Mader
Pubblicato in: IEEE Intelligent Transportation Systems Conference (ITSC), 2021
Editore: IEEE
DOI: 10.48550/arxiv.2104.10780

SENeCA: Scalable Energy-efficient Neuromorphic Computer Architecture

Autori: A. Yousefzadeh, G.-J. van Schaik, M. Tahghighi, P. Detterer, S. Traferro, M. Hijdra, J. Stuijt, F. Corradi, M. Sifalakis, M. Konijnenburg
Pubblicato in: Artificial Intelligence Circuit and Systems (AICAS), 2022
Editore: IEEE
DOI: 10.1109/aicas54282.2022.9870025

Influence of microstructure on the variability and current percolation paths in ferroelectric hafnium oxide based neuromorphic FeFET synapses

Autori: M. Lederer, F. Müller, A. Varanasi, R. Olivo, K. Mertens, D. Lehninger, Y. Raffel, R. Hoffmann, T. Ali, K. Seidel, T. Kämpfe, L.M. Eng
Pubblicato in: Silicon Nanoelectronics Workshop (SNW), 2021
Editore: IEEE
DOI: 10.1109/snw51795.2021.00033

A comparative study on Unsupervised Deep Learning Methods for X-Ray Image Denoising with Multi-Image Self2Self and Single Frequency Denoising

Autori: Cagla Sozen
Pubblicato in: MSc dissertation, 2022
Editore: TUe

Electron Devices based on Ferroelectric Hafnium Oxide

Autori: Thomas Kämpfe
Pubblicato in: Thesis (habilitation), 2022
Editore: ResearchGate

Poster on SENeCA, Tempo

Autori: G. van Schaik
Pubblicato in: ICT.OPEN2022, 2022
Editore: ictopen.nl

The international workshop on edge artificial intelligence for industrial applications (EAI4IA)

Autori: AI4DI, TEMPO, ANDANTE
Pubblicato in: Workshop announcement, 2022
Editore: vimeo

Stromsparende Chips für Künstliche Intelligenz

Autori: TEMPO consortium
Pubblicato in: Press release Fraunhofer Journal, 2020
Editore: Fraunhofer Journal

TEMPO booth poster

Autori: G. van Schaik
Pubblicato in: Neuromorphic Computing Netherlands (NCN2021), 2021
Editore: cwi

Ultra-Low Power Computing with AI

Autori: Thomas Kämpfe
Pubblicato in: WIOT Day Automotive & IIOT Livestream, 2022
Editore: WIOT Day Automotive & IIOT

Bio-inspired neuromorphic circuits architectures

Autori: Giacomo Indiveri
Pubblicato in: tinyML EMEA Technical Forum, 2021
Editore: tinyML

Efficient hardware approximation for bit-decomposition based Deep Neural Network

Autori: T. Soliman, A. Eldebiky, C. De La Parra, A. Guntoro, N. Wehn
Pubblicato in: Design Automation Conference (DAC), 2021
Editore: IEEE

Embedded Artificial Intelligence (EAI) – Devices, Systems, and Industrial Applications

Autori: AI4DI, TEMPO, ANDANTE
Pubblicato in: Workshop announcement, 2022
Editore: vimeo

TEMPO AI chip tapes out with videantis processor platform

Autori: Videantis
Pubblicato in: Press release videantis, 2022
Editore: Videantis

Technologies and hardware for neuromorphic computing

Autori: Björn Debaillie
Pubblicato in: The international workshop on edge artificial intelligence for industrial applications (EAI4IA), 2022
Editore: TEMPO

Neuromorphic Intelligence: brain inspired artificial intelligence circuits and systems for extreme edge computing applications

Autori: Giacomo Indiveri
Pubblicato in: Invited lecture Dipartimento Politecnico di Ingegneria e Architettura, University of Udine, 2021
Editore: University of Udine

Poster on SENeCA, Tempo

Autori: A. Yousefzadeh
Pubblicato in: TinyML summit 2022, 2022
Editore: TinyML

Neuromorphic Intelligence: brain-inspired strategies for efficient computation in spiking neural networks

Autori: Giacomo Indiveri
Pubblicato in: International Workshop on Artificial life and evolutionary computation, 2021
Editore: International Workshop on Artificial life and evolutionary computation

How to get a server rack in your back pocket?

Autori: TEMPO consortium
Pubblicato in: Imec press release, 2019
Editore: imec

Technologies and hardware for neuromorphic computing

Autori: Thomas Kämpfe
Pubblicato in: International Conference on IC Design and Technology, 2022
Editore: IEEE

SynSense joins TEMPO, a large EU-funded industry consortium for Neuromorphic technology

Autori: SynSense
Pubblicato in: SynSense press release, 2019
Editore: SynSense

Industrial Artificial Intelligence Technologies and Applications

Autori: Ovidiu Vermesan, Franz Wotawa, Mario Diaz Nava, Björn Debaillie
Pubblicato in: Industrial Artificial Intelligence Technologies and Applications, 2022
Editore: River Publishers
DOI: 10.13052/rp-9788770227902

Embedded Artificial Intelligence (EAI) – Devices, Systems, and Industrial Applications

Autori: Ovidiu Vermesan, Björn Debaillie, Mario Diaz Nava
Pubblicato in: Embedded Artificial Intelligence, 2022
Editore: River Publishers

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