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Block-Quantized and Data-Efficient Deep Learning at the Edge: Optimizing Deployments with General-Purpose and Domain-Specific Vector Instruction Sets Nitish Satya Murthy · Dissertation · 2025
The neurobench framework for benchmarking neuromorphic computing algorithms and systems Jason Yik, Korneel van den Berghe, Douwe den Blanken, Younes Bouhadjar, Maxime Fabre, Paul Hueber, Weijie Ke, Mina A Khoei, Denis Kleyko, Noah Pacik-Nelson, Alessandro Pierro, Philipp Stratmann, Pao-Sheng Vincent Sun, Guangzhi Tang, Shenqi Wang, Biyan Zhou, Soikat Hasan Ahmed, George Vathakkattil Joseph, Benedetto Leto, Aurora Micheli, Anurag Kumar Mishra, Gregor Lenz, Tao Sun, Zergham Ahmed, Mahmoud Akl, Brian Anderson, Andreas G Andreou, Chiara Bartolozzi, Arindam Basu, Petrut Bogdan, Sander Bohte, Sonia Buckley, Gert Cauwenberghs, Elisabetta Chicca, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Tobias Fischer, Jeremy Forest, Vittorio Fra, Steve Furber, P Michael Furlong, William Gilpin, Aditya Gilra, Hector A Gonzalez, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Shih-Chii Liu, Yao-Hong Liu, Haoyuan Ma, Rajit Manohar, Josep Maria Margarit-Taule, Christian Mayr, Konstantinos Michmizos, Dylan R Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayca Ozcelikkale, Priyadarshini Panda, Jongkil Park, Melika Payvand, Christian Pehle, Mihai A Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, Andre van Schaik, Johannes Schemmel, Samuel Schmidgall, Catherine Schuman, Jae-sun Seo, Sadique Sheik, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Stewart, Matthew Stewart, Terrence C Stewart, Jonathan Timcheck, Nergis Tomen, Gianvito Urgese, Marian Verhelst, Craig M Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Fatima Tuz Zohora, Charlotte Frenkel, and Vijay Janapa Reddi · Journal Article · 2025 Nature Communications; 2025; Vol. 16; iss. 1
Michiel in a Team of Colleagues: MICAS, Matching, mm-Wave, Mentor: How a colorful career in IC research has led to a huge impact on research and education Patrick Reynaert, Wim Dehaene, Filip Tavernier, Georges Gielen, and Marian Verhelst · Journal Article · 2025 IEEE Xplore; 2025; Vol. 17; iss. 1; pp. 33 - 39
Hardware Modeling and Exploration Towards Edge AI Acceleration Pouya Houshmand · Dissertation · 2025
2024 IEEE European Solid-State Electronics Research Conference Wim Dehaene, Michiel Steyaert, Patrick Reynaert, Filip Tavernier, Anne Verhulst, James Myers, Marian Verhelst, Georges Gielen, Cor Claeys, and Ann Naeye · Conference Proceeding · 2025 IEEE Solid State Circuits Magazine; 2025; Vol. 17; iss. 1; pp. 134 - 135
Quantized Dynamics Models for Hardware-Efficient Control and Planning in Model-Based RL Nitish Satya Murthy, Francky Catthoor, Marian Verhelst, and Peter Vrancx · Conference Proceeding · 2025 Machine Learning and Principles and Practice of Knowledge Discovery in Databases; 2025; pp. 196 - 209
Stream: Design Space Exploration of Layer-fused DNNs on Heterogeneous Dataflow Accelerators Arne Symons, Linyan Mei, Steven Colleman, Pouya Houshmand, Sebastian Karl, and Marian Verhelst · Journal Article · 2025 IEEE Transactions On Computers; 2025; Vol. 74; iss. 1; pp. 237 - 249
Adaptive Block-Scaled GeMMs on Vector Processors for DNN Training at the Edge Nitish Satya Murthy, Nathan Laubeuf, Debjyoti Bhattacharjee, Francky Catthoor, and Marian Verhelst · Conference Proceeding · 2024 2024 IFIP/IEEE 32nd International Conference on Very Large Scale Integration (VLSI-SoC); 2024; pp. 1 - 6
Energy Cost Modelling for Optimizing Large Language Model Inference on Hardware Accelerators Robin Geens, Man Shi, Arne Symons, Chao Fang, and Marian Verhelst · Conference Proceeding · 2024 2024 IEEE 37th International System-on-Chip Conference (SOCC); 2024
AIA: A 16nm Multicore SoC for Approximate Inference Acceleration Exploiting Non-normalized Knuth-Yao Sampling and Inter-Core Register Sharing Shirui Zhao, Nimish Shah, Wannes Meert, and Marian Verhelst · Conference Proceeding · 2024 2024 IEEE European Solid-State Electronics Research Conference (ESSERC); 2024; pp. 29 - 32
Optimization of block-scaled integer GeMMs for efficient DNN deployment on scalable in-order vector processors Nitish Satya Murthy, Francky Catthoor, and Marian Verhelst · Journal Article · 2024 Journal Of Systems Architecture; 2024; Vol. 154
Hardware–Software Co-optimization Through Design Space Exploration Vikram Jain and Marian Verhelst · Book Chapter · 2024 Towards Heterogeneous Multi-core Systems-on-Chip for Edge Machine Learning: Journey from Single-core Acceleration to Multi-core Heterogeneous Systems; 2024; pp. 59 - 69
TinyML4D: Scaling Embedded Machine Learning Education in the Developing World Brian Plancher, Sebastian Buttrich, Jeremy Ellis, Neena Goveas, Laila Kazimierski, Jesus Lopez Sotelo, Milan Lukic, Diego Mendez, Rosdiadee Nordin, Andres Oliva Trevisan, Massimo Pavan, Manuel Roveri, Marcus Rüb, Jackline Tum, and Marian Verhelst · Journal Article · 2024 Proceedings of the AAAI symposium series; 2024; Vol. 3; iss. 1; pp. 508 - 515
Modeling and Analysis for Efficient Hardware Mapping of Neural Network Algorithms Steven Colleman · Dissertation · 2024
TreeGRNG: Binary Tree Gaussian Random Number Generator for Efficient Probabilistic AI Hardware Jonas Crols, Guilherme Paim, Shirui Zhao, and Marian Verhelst · Conference Proceeding · 2024 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE); 2024; pp. 1 - 6
BitWave: Exploiting Column-Based Bit-Level Sparsity for Deep Learning Acceleration Man Shi, Vikram Jain, Antony Joseph, Maurice Meijer, and Marian Verhelst · Conference Proceeding · 2024 2024 IEEE INTERNATIONAL SYMPOSIUM ON HIGH-PERFORMANCE COMPUTER ARCHITECTURE, HPCA 2024; 2024; pp. 732 - 746
Optimizing Layer-Fused Scheduling of Transformer Networks on Multi-accelerator Platforms Steven Colleman, Arne Symons, Victor JB Jung, and Marian Verhelst · Conference Proceeding · 2024 2024 25th International Symposium on Quality Electronic Design (ISQED); 2024
Enabling Efficient Hardware Acceleration of Hybrid Vision Transformer (ViT) Networks at the Edge Joren Dumoulin, Pouya Houshmand, Vikram Jain, and Marian Verhelst · Conference Proceeding · 2024 2024 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, ISCAS 2024; 2024
High-rate, compact in-sensor denoising for active stereo vision towards embedded depth sensing Pouya Houshmand, Jean-Sebastien Staelens, Ward van der Tempe, and Marian Verhelst · Conference Proceeding · 2024 2024 22ND IEEE INTERREGIONAL NEWCAS CONFERENCE, NEWCAS 2024; 2024; pp. 11 - 15
HUNBN, a 1.77MB Digital In-Memory-Compute SoC for edge applications achieving 126 TOPs/W (4b) at macro level and 24 TOPs/W at SoC level. Weijie Jiang, Cedric Caron, Prabhat Avasare, Marc Pauwels, Marian Verhelst, and Wim Dehaene · Conference Proceeding · 2024 2024 IEEE European Solid-State Electronics Research Conference (ESSERC); 2024; pp. 137 - 140
System-Technology Co-Optimization for Dense Edge Architectures Using 3-D Integration and Nonvolatile Memory Leandro M Giacomini Rocha, Mohamed Naeim, Guilherme Paim, Moritz Brunion, Priya Venugopal, Dragomir Milojevic, James Myers, Mustafa Badaroglu, Marian Verhelst, Julien Ryckaert, and Dwaipayan Biswas · Journal Article · 2024 IEEE Journal on Exploratory Solid-State Computational Devices and Circuits; 2024; Vol. 10; pp. 125 - 134
Resource-Constrained Training of Deep Neural Networks for Industrial Computer Vision Applications Robby Neven · Dissertation · 2023
Microelectronics for Microbiology Peishuo Li · Dissertation · 2023
The “Eagle” Approach To Train Electrical Engineers With Collaborative Problem-Solving Skills Fereshteh Poormohammadi, Merijn Van Deyck, Martijn Deckers, Abdul Saboor, Bowen Wang, Pouya Mehrjouseresht, Zhenda Zhang, Arne Symons, Pieter Pas, Alexander Bodard, Hans van Rooij, Marian Verhelst, Alexander Bertrand, Ruth Sabariego, Panagiotis Patrinos, and Peter Coppens · Conference Proceeding · 2023 51st Annual Conference of the European Society for Engineering Education (SEFI); 2023; pp.
An Online-Spike-Sorting IC Using Unsupervised Geometry-Aware OSort Clustering for Efficient Embedded Neural-Signal Processing Yingping Chen, Bernardo Tacca, Yunzhu Chen, Dwaipayan Biswas, Georges Gielen, Francky Catthoor, Marian Verhelst, and Carolina Mora Lopez · Journal Article · 2023 IEEE Xplore; 2023; Vol. 58; iss. 11; pp.
Design Space Exploration of Deep Learning Accelerators Linyan Mei · Dissertation · 2023
Ultrasound In-Body Communication: Channels, Modems and Hardware for Ultrasound In-Body Communication Links Thomas Bos · Dissertation · 2023
An End-to-End Dual ASIC OFDM Transceiver for Ultrasound In-Body Communication Thomas Bos, Marian Verhelst, and Wim Dehaene · Journal Article · 2023 IEEE Transactions On Biomedical Circuits And Systems; 2023; Vol. 17; iss. 4; pp. 664 - 673
COAC: Cross-Layer Optimization of Accelerator Configurability for Efficient CNN Processing Steven Colleman, Man Shi, and Marian Verhelst · Journal Article · 2023 IEEE Transactions On Very Large Scale Integration (Vlsi) Systems; 2023; Vol. 31; iss. 7; pp. 945 - 958
Towards Heterogeneous Multi-core Systems-on-Chip for Edge Machine Learning Vikram Jain · Dissertation · 2023
DepFiN: A 12-nm Depth-First, High-Resolution CNN Processor for IO-Efficient Inference Koen Goetschalckx, Fengfeng Wu, and Marian Verhelst · Journal Article · 2023 IEEE Journal Of Solid-State Circuits; 2023; Vol. 58; iss. 5; pp.
CNN-based Robust Sound Source Localization with SRP-PHAT for the Extreme Edge Jun Yin and Marian Verhelst · Journal Article · 2023 Acm Transactions On Embedded Computing Systems; 2023; Vol. 22; iss. 3; pp.
Optimizing Embedded Vision Efficiency across the Hardware-dataflow-algorithm Stack Koen Goetschalckx · Dissertation · 2023
Ultra Low Power Adaptive Sensor Nodes Jaro De Roose · Dissertation · 2023
Efficient Execution of Irregular Dataflow Graphs: Hardware/Software Co-optimization for Probabilistic AI and Sparse Triangular Systems Nimish Shirishbhai Shah · Dissertation · 2023
TinyVers: A Tiny Versatile System-on-Chip With State-Retentive eMRAM for ML Inference at the Extreme Edge Vikram Jain, Sebastian Giraldo, Jaro De Roose, Linyan Mei, Bert Boons, and Marian Verhelst · Journal Article · 2023 IEEE Journal Of Solid-State Circuits; 2023; Vol. 58; iss. 8; pp. 1 - 12
A 96-channel 40nm CMOS Potentiostat for Parallel Experiments on Microbial Electrochemical Systems Peishuo Li, Tom Molderez, David Villamor, Antonin Prévoteau, and Marian Verhelst · Journal Article · 2023 IEEE Transactions On Circuits And Systems I-Regular Papers; 2023; Vol. 70; iss. 1; pp.
DIANA: An End-to-End Hybrid DIgital and ANAlog Neural Network SoC for the Edge Pouya Houshmand, Giuseppe M Sarda, Vikram Jain, Kodai Ueyoshi, Ioannis A Papistas, Man Shi, Qilin Zheng, Debjyoti Bhattacharjee, Arindam Mallik, Peter Debacker, Diederik Verkest, and Marian Verhelst · Journal Article · 2023 IEEE Journal Of Solid-State Circuits; 2023; Vol. 58; iss. 1; pp. 203 - 215
DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling Linyan Mei, Koen Goetschalckx, Arne Symons, and Marian Verhelst · Conference Proceeding · 2023 2023 IEEE INTERNATIONAL SYMPOSIUM ON HIGH-PERFORMANCE COMPUTER ARCHITECTURE, HPCA; 2023; pp. 570 - 583
Stream: A Modeling Framework for Fine-grained Layer Fusion on Multi-core DNN Accelerators Arne Symons, Linyan Mei, Steven Colleman, Pouya Houshmand, Sebastian Karl, and Marian Verhelst · Conference Proceeding · 2023 2023 IEEE INTERNATIONAL SYMPOSIUM ON PERFORMANCE ANALYSIS OF SYSTEMS AND SOFTWARE, ISPASS; 2023; pp. 355 - 357
CMDS: Cross-layer Dataflow Optimization for DNN Accelerators Exploiting Multi-bank Memories Man Shi, Steven Colleman, Charlotte VanDeMieroop, Antony Joseph, Maurice Meijer, Wim Dehaene, and Marian Verhelst · Conference Proceeding · 2023 2023 24TH INTERNATIONAL SYMPOSIUM ON QUALITY ELECTRONIC DESIGN, ISQED; 2023; pp. 172 - 179
Genetic Algorithm-based Framework for Layer-Fused Scheduling of Multiple DNNs on Multi-core Systems Sebastian Karl, Arne Symons, Nael Fasfous, and Marian Verhelst · Conference Proceeding · 2023 2023 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION, DATE; 2023; pp.
PetaOps/W edge-AI μProcessors: Myth or reality? Manil Dev Gomony, Floran de Putter, Anteneh Gebregiorgis, Gianna Paulin, Linyan Mei, Vikram Jain, Said Hamdioui, Victor Sanchez, Tobias Grosser, Marc Geilen, Marian Verhelst, Friedemann Zenke, Frank Gurkaynak, Barry de Bruin, Sander Stuijk, Simon Davidson, Sayandip De, Mounir Ghogho, Alexandra Jimborean, Sherif Eissa, Luca Benini, Dimitrios Soudris, Rajendra Bishnoi, Sam Ainsworth, Federico Corradi, Ouassim Karrakchou, Tim Gueneysu, and Henk Corporaal · Conference Proceeding · 2023 2023 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION, DATE; 2023; pp.
A 16nm 128kB high-density fully digital In Memory Compute macro with reverse SRAM pre-charge achieving 0.36TOPs/mm2, 256kB/mm2 and 23. 8TOPs/W Weijie Jiang, Pouya Houshmand, Marian Verhelst, and wim Dehaene · Conference Proceeding · 2023 ESSCIRC 2023- IEEE 49th European Solid State Circuits Conference (ESSCIRC); 2023; pp. 409 - 412
Precision-aware Latency and Energy Balancing on Multi-Accelerator Platforms for DNN Inference Matteo Risso, Alessio Burrello, Giuseppe Maria Sarda, Luca Benini, Enrico Macii, Massimo Poncino, Marian Verhelst, and Daniele Jahier Pagliari · Conference Proceeding · 2023 2023 IEEE/ACM INTERNATIONAL SYMPOSIUM ON LOW POWER ELECTRONICS AND DESIGN, ISLPED; 2023; pp.
HTVM: Efficient Neural Network Deployment On Heterogeneous TinyML Platforms Josse Van Delm, Maarten Vandersteegenl, Alessio Burrello, Giuseppe Maria Sarda, Francesco Conti, Daniele Jahier Pagliari, Luca Benini, and Marian Verhelst · Conference Proceeding · 2023 2023 60TH ACM/IEEE DESIGN AUTOMATION CONFERENCE, DAC; 2023; pp.
PATRONoC: Parallel AXI Transport Reducing Overhead for Networks-on-Chip targeting Multi-Accelerator DNN Platforms at the Edge Vikram Jain, Matheus Cavalcante, Nazareno Bruschi, Michael Rogenmoser, Thomas Benz, Andreas Kurth, Davide Rossi, Luca Benini, and Marian Verhelst · Conference Proceeding · 2023 2023 60TH ACM/IEEE DESIGN AUTOMATION CONFERENCE, DAC; 2023; pp.
GRAPHOPT: constrained-optimization-based parallelization of irregular graphs Nimish Shirishbhai Shah, Wannes Meert, and Marian Verhelst · Journal Article · 2022 IEEE Transactions On Parallel And Distributed Systems; 2022; Vol. 33; iss. 12; pp. 3321 - 3332
Hardware-Aware Mobile Building Block Evaluation for Computer Vision Maxim Bonnaerens, Matthias Freiberger, Marian Verhelst, and Joni Dambre · Journal Article · 2022 Applied Sciences-Basel; 2022; Vol. 12; iss. 24; pp.
A Flexible End-to-End Dual ASIC Transceiver for OFDM Ultrasound In-Body Communication Thomas Bos, Marian Verhelst, and Wim Dehaene · Conference Proceeding · 2022 2022 IEEE Biomedical Circuits and Systems Conference (BioCAS); 2022; pp. 21 - 25
DPU: DAG Processing Unit for Irregular Graphs With Precision-Scalable Posit Arithmetic in 28 nm Nimish Shirishbhai Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, and Marian Verhelst · Journal Article · 2022 IEEE Journal Of Solid-State Circuits; 2022; Vol. 57; iss. 8; pp. 1 - 11
TinyVers: A 0.8-17 TOPS/W, 1.7 μW-20 mW, Tiny Versatile System-on-chip with State-Retentive eMRAM for Machine Learning Inference at the Extreme Edge Vikram Jain, Sebastian Giraldo, Jaro De Roose, Bert Boons, Linyan Mei, and Marian Verhelst · Conference Proceeding · 2022 2022 IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits); 2022; pp.
Graph Analytics on RISC-V GPU: Where are the Bottlenecks? Nimish Shah and Marian Verhelst · Other · 2022
Fair and Comprehensive Benchmarking of Machine Learning Processing Chips Geoffrey W Burr, SukHwan Lim, Boris Murmann, Rangharajan Venkatesan, and Marian Verhelst · Journal Article · 2022 IEEE Design & Test; 2022; Vol. 39; iss. 3; pp. 18 - 27
Towards the next generation Heterogeneous Multi-core Multi-accelerator Architectures for Machine Learning Vikram Jain, Giuseppe Sarda, Pouya Houshmand, and Marian Verhelst · Other · 2022
Taxonomy and Benchmarking of Precision-Scalable MAC Arrays Under Enhanced DNN Dataflow Representation Ehab M Ibrahim, Linyan Mei, and Marian Verhelst · Journal Article · 2022 IEEE Transactions On Circuits And Systems I-Regular Papers; 2022; Vol. 69; iss. 5; pp. 2013 - 2024
DIANA: An End-to-End Energy-Efficient Digital and ANAlog Hybrid Neural Network SoC Kodai Ueyoshi, Ioannis A Papistas, Pouya Houshmand, Giuseppe Maria Sarda, Vikram Jain, man Shi, Qilin Zheng, Sebastian Giraldo, Peter Vranckx, Jonas Doevenspeck, Debjyoti Bhattacharjee, Stefan Cosemans, Arindam Mallik, Peter Debacker, Diederik Verkest, and Marian Verhelst · Conference Proceeding · 2022 2022 IEEE International Conference on Solid-State Circuits (ISSCC); 2022; Vol. 65; pp.
VERSA: A 0.8-17.1 TOPS/W, 1.68 uW-20 mW, versatile system-on-chip with state-retentive eMRAM for machine learning inference Vikram Jain, Sebastian Giraldo, and Marian Verhelst · Other · 2022
Enabling real-time object detection on low cost FPGAs Vikram Jain, Ninad Jadhav, and Marian Verhelst · Journal Article · 2022 Journal Of Real-Time Image Processing; 2022; Vol. 19; iss. 1; pp. 217 - 229
Optimizing Accelerator Configurability for Mobile Transformer Networks Steven Colleman, Peter Zhu, Wei Sun, and Marian Verhelst · Conference Proceeding · 2022 2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS); 2022; pp. 142 - 145
A Uniform Latency Model for DNN Accelerators with Diverse Architectures and Dataflows Linyan Mei, Huichu Liu, Tony Wu, H Ekin Sumbul, Marian Verhelst, and Edith Beigne · Conference Proceeding · 2022 Proceedings of the 2022 Design, Automation & Test in Europe (DATE 2022); 2022; pp. 220 - 225
Discrete Samplers for Approximate Inference in Probabilistic Machine learning Shirui Zhao, Nimish Shah, Wannes Meert, and Marian Verhelst · Conference Proceeding · 2022 Design, Automation and Test in Europe Conference and Exhibition (DATE), 2022; 2022; pp. 1221 - 1226
Learn to Learn on Chip: Hardware-aware Meta-learning for Quantized Few-shot Learning at the Edge Nitish Satya Murthy, Peter Vrancx, Nathan Laubeuf, Peter Debacker, Francky Catthoor, and Marian Verhelst · Conference Proceeding · 2022 2022 IEEE/ACM 7TH SYMPOSIUM ON EDGE COMPUTING (SEC 2022); 2022; pp. 14 - 25
DPU-v2: Energy-efficient execution of irregular directed acyclic graphs Nimish Shah, Wannes Meert, and Marian Verhelst · Conference Proceeding · 2022 2022 55TH ANNUAL IEEE/ACM INTERNATIONAL SYMPOSIUM ON MICROARCHITECTURE (MICRO); 2022; pp. 1288 - 1307
Impact of Emerging Electrical and Optical 3D Integration Technologies on High Bandwidth Interconnect Systems Nicolas Pantano · Dissertation · 2021
Hardware-Efficient Residual Neural Network Execution in Line-Buffer Depth-First Processing Man Shi, Pouya Houshmand, Linyan Mei, and Marian Verhelst · Journal Article · 2021 IEEE Journal On Emerging And Selected Topics In Circuits And Systems; 2021; Vol. 11; iss. 4; pp. 690 - 700
Efficient Execution of Temporal Convolutional Networks for Embedded Keyword Spotting JSP Giraldo, Vikram Jain, and Marian Verhelst · Journal Article · 2021 IEEE Transactions On Very Large Scale Integration (Vlsi) Systems; 2021; Vol. 29; iss. 12; pp. 1 - 9
A 96-channel 40nm CMOS Fully-Integrated Potentiostat for Electrochemical Monitoring Peishuo Li, Tom Molderez, and Marian Verhelst · Conference Proceeding · 2021 ESSCIRC 2021 - IEEE 47th European Solid State Circuits Conference (ESSCIRC); 2021; pp. 167 - 170
Embedded ML for Efficient Keyword Spotting Juan Sebastian Piedrahita Giraldo · Dissertation · 2021
ZigZag: Enlarging Joint Architecture-Mapping Design Space Exploration for DNN Accelerators Linyan Mei, Pouya Houshmand, Vikram Jain, Sebastian Giraldo, and Marian Verhelst · Journal Article · 2021 IEEE Transactions On Computers; 2021; Vol. 70; iss. 8; pp. 1160 - 1174
DepFiN: A 12nm, 3.8TOPs depth-first CNN processor for high res. image processing Koen Goetschalckx and Marian Verhelst · Conference Proceeding · 2021 2021 Symposium on VLSI Circuits; 2021; pp. 1 - 2
Analyzing the Energy-Latency-Area-Accuracy Trade-off Across Contemporary Neural Networks Vikram Jain, linyan Mei, and Marian Verhelst · Conference Proceeding · 2021 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS); 2021; pp.
Highly Parallel Architectures – Programmable Pipeline Systems as a Solution to the Memory Bottleneck Sander Smets · Dissertation · 2021
Performance analysis of in-band collision detection for dense wireless networks Tom Vermeulen, Brecht Reynders, Fernando E Rosas, Marian Verhelst, and Sofie Pollin · Journal Article · 2021 Eurasip Journal On Wireless Communications And Networking; 2021; Vol. 2021; iss. 1; pp.
A Scalable 128-channel, Time-multiplexed Potentiostat for Parallel Electrochemical Experiments Tom R Molderez, Korneel Rabaey, and Marian Verhelst · Journal Article · 2021 IEEE Transactions On Circuits And Systems I-Regular Papers; 2021; Vol. 68; iss. 3; pp. 1068 - 1079
A chip-based 128-channel potentiostat for high-throughput studies of bioelectrochemical systems: Optimal electrode potentials for anodic biofilms Tom Molderez, Antonin Prévoteau, Frederik Ceyssens, Marian Verhelst, and Korneel Rabaey · Journal Article · 2021 Biosensors & Bioelectronics; 2021; Vol. 174; pp.
Microelectronics for Microorganisms: Measurement Instrumentation and Optimization Algorithms for Electroactive Biofilms Tom Molderez · Dissertation · 2021
High-Utilization, High-Flexibility Depth-First CNN Coprocessor for Image Pixel Processing on FPGA Steven Colleman and Marian Verhelst · Journal Article · 2021 IEEE Transactions On Very Large Scale Integration (Vlsi) Systems; 2021; Vol. 29; iss. 3; pp. 461 - 471
Dynamic Complexity Tuning for Hardware-Aware Probabilistic Circuits Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, and Marian Verhelst · Conference Proceeding · 2021 IoT Streams for Data-Driven Predictive Maintenance and IoT, Edge, and Mobile for Embedded Machine Learning; 2021; pp. 283 - 295
Processor Architecture Optimization for Spatially Dynamic Neural Networks Steven Colleman, Thomas Verelst, Linyan Mei, Tinne Tuytelaars, and Marian Verhelst · Conference Proceeding · 2021 2021 IFIP/IEEE 29th International Conference on Very Large Scale Integration (VLSI-SoC); 2021; pp.
LOMA: Fast Auto-Scheduling on DNN Accelerators through Loop-Order-based Memory Allocation Arne Symons, Linyan Mei, and Marian Verhelst · Conference Proceeding · 2021 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS); 2021; pp. 1 - 4
PIU: A 248GOPS/W Stream-Based Processor for Irregular Probabilistic Inference Networks Using Precision-Scalable Posit Arithmetic in 28nm Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, and Marian Verhelst · Conference Proceeding · 2021 Proceedings of 2021 IEEE International Solid- State Circuits Conference (ISSCC); 2021; Vol. 64; pp. 1 - 3
PeakRNN and StatsRNN: Dynamic Pruning in Recurrent Neural Networks Zuzana Jelcicova, Rasmus Jones, David Thorn Blix, Marian Verhelst, and Jens Sparso · Conference Proceeding · 2021 29TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2021); 2021; pp. 416 - 420
A 96-channel 40nm CMOS Fully-Integrated Potentiostat for Electrochemical Monitoring Peishuo Li, Tom R Molderez, and Marian Verhelst · Conference Proceeding · 2021 IEEE 51ST EUROPEAN SOLID-STATE DEVICE RESEARCH CONFERENCE (ESSDERC 2021); 2021; pp. 167 - 170
Hardware-Aware Probabilistic Models: Learning, Inference and Use Cases Laura Isabel Galindez Olascoaga · Dissertation · 2020
Flexible, Self-adaptive Sense-and-Compress SoC for sub-microWatt always-on sensory recording Jaro De Roose, Haoming Xin, Ahmed Hallawa, Gerd Ascheid, Pieter Harpe, and Marian Verhelst · Journal Article · 2020 IEEE Solid State Circuits Letters; 2020; Vol. 3; pp. 362 - 365
Modeling and Optimization of Hybrid FinFET-Silicon Photonic Interconnects Nicolas Pantano, Michal Rakowski, Davide Guermandi, Marian Verhelst, and Joris Van Campenhout · Journal Article · 2020 Journal Of Lightwave Technology; 2020; Vol. 38; iss. 16; pp. 4325 - 4332
Binary CorNET: Accelerator for HR Estimation From Wrist-PPG Leandro Giacomini Rocha, Dwaipayan Biswas, Bram-Ernst Verhoef, Sergio Bampi, Chris Van Hoof, Mario Konijnenburg, Marian Verhelst, and Nick Van Helleputte · Journal Article · 2020 IEEE Transactions On Biomedical Circuits And Systems; 2020; Vol. 14; iss. 4; pp. 715 - 726
A 28-nm Coarse Grain 2D-Reconfigurable Array With Data Forwarding S Smets, MD Gormony, M Jivanescu, T Goedemé, and Marian Verhelst · Journal Article · 2020 IEEE Solid State Circuits Letters; 2020; Vol. 3; pp. 226 - 229
A 5-GS/s 158.6-mW 9.4-ENOB Passive-Sampling Time-Interleaved Three-Stage Pipelined-SAR ADC With Analog-Digital Corrections in 28-nm CMOS Athanasios T Ramkaj, Juan C Pena Ramos, Marcel JM Pelgrom, Michiel SJ Steyaert, Marian Verhelst, and Filip Tavernier · Journal Article · 2020 IEEE Journal Of Solid-State Circuits; 2020; Vol. 55; iss. 6; pp. 1553 - 1564
Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, and Marian Verhelst · Conference Proceeding · 2020 Advances in Intelligent Data Analysis XVIII; 2020; Vol. 12080; pp. 184 - 196
Vocell: A 65-nm Speech-Triggered Wake-Up SoC for 10-μW Keyword Spotting and Speaker Verification Juan Sebastian Piedrahita Giraldo, Steven Lauwereins, Komail Badami, and Marian Verhelst · Journal Article · 2020 IEEE Journal Of Solid-State Circuits; 2020; Vol. 55; iss. 4; pp.
Machine Learning at the Edge Marian Verhelst and Boris Murmann · Book Chapter · 2020 NANO-CHIPS 2030; 2020; pp. 293 - 322
Feed-forward on-edge fine-tuning using static synthetic gradient modules Robby Neven, Marian Verhelst, Tinne Tuytelaars, and Toon Goedemé · Conference Proceeding · 2020 Lecture Notes in Computer Science - Computer Vision – ECCV 2020 Workshops; 2020; Vol. 12539; pp. 131 - 146
Opportunities and Limitations of Emerging Analog in-Memory Compute DNN Architectures Pouya Houshmand, Stefan Cosemans, Linyan Mei, Ioannis Papistas, Debjyoti Bhattacharjee, Peter Debacker, Arindam Mallik, Diederik Verkest, and Marian Verhelst · Conference Proceeding · 2020 2020 IEEE INTERNATIONAL ELECTRON DEVICES MEETING (IEDM); 2020; pp.
Whitepaper AI at the edge - a roadmap Jan Rabaey, Marian Verhelst, Jo De Boeck, C Enz, Kristiaan De Greve, Adrian Ionescu, Myunhee Na, and Kathleen Philips · Other · 2020
DVAFS—Dynamic-Voltage-Accuracy-Frequency-Scaling Applied to Scalable Convolutional Neural Network Acceleration Bert Moons and Marian Verhelst · Book Chapter · 2020 System-Scenario-based Design Principles and Applications; 2020; pp. 99 - 111
On the convexity of bit depth allocation for linear MMSE estimation in wireless sensor networks F de la Hucha Arce, Panagiotis Patrinos, M Verhelst, and A Bertrand · Journal Article · 2020 IEEE Signal Processing Letters; 2020; Vol. 27; pp. 291 - 295
Distributed adaptive node-specific signal estimation in a wireless sensor network with noisy links Fernando de la Hucha Arce, M Moonen, M Verhelst, and A Bertrand · Journal Article · 2020 Signal Processing; 2020; Vol. 166; pp.
Acceleration of probabilistic reasoning through custom processor architecture Nimish Shirishbhai Shah, Laura I Galindez Olascoaga, Wannes Meert, and Marian Verhelst · Conference Proceeding · 2020 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE); 2020; pp. 322 - 325