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2020 – today
- 2025
[j67]Arne Symons
, Linyan Mei, Steven Colleman, Pouya Houshmand, Sebastian Karl, Marian Verhelst:
Stream: Design Space Exploration of Layer-Fused DNNs on Heterogeneous Dataflow Accelerators. IEEE Trans. Computers 74(1): 237-249 (2025)- [c140]Xiaoling Yi, Ryan Antonio, Joren Dumoulin, Jiacong Sun, Josse Van Delm, Guilherme Pereira Paim, Marian Verhelst:
OpenGeMM: A Highly-Efficient GeMM Accelerator Generator with Lightweight RISC-V Control and Tight Memory Coupling. ASP-DAC 2025: 1055-1061 - [c139]Alexandre Lopoukhine, Federico Ficarelli, Christos Vasiladiotis, Anton Lydike, Josse Van Delm, Alban Dutilleul, Luca Benini, Marian Verhelst, Tobias Grosser:
A Multi-level Compiler Backend for Accelerated Micro-kernels Targeting RISC-V ISA Extensions. CGO 2025: 163-178 - [i38]Alexandre Lopoukhine, Federico Ficarelli, Christos Vasiladiotis, Anton Lydike, Josse Van Delm, Alban Dutilleul, Luca Benini, Marian Verhelst, Tobias Grosser:
A Multi-level Compiler Backend for Accelerated Micro-kernels Targeting RISC-V ISA Extensions. CoRR abs/2502.04063 (2025) - 2024
- [j66]Nitish Satya Murthy, Francky Catthoor, Marian Verhelst:
Optimization of block-scaled integer GeMMs for efficient DNN deployment on scalable in-order vector processors. J. Syst. Archit. 154: 103236 (2024) - [c138]Brian Plancher, Sebastian Büttrich, Jeremy Ellis, Neena Goveas, Laila D. Kazimierski, Jesús Alfonso López Sotelo, Milan Lukic, Diego Mendez, Rosdiadee Nordin, Andrés Oliva Trevisan, Massimo Pavan, Manuel Roveri, Marcus Rüb, Jackline Tum, Marian Verhelst, Salah Abdeljabar, Segun Adebayo, Thomas Amberg, Halleluyah Aworinde, José Bagur, Gregg Barrett, Nabil Benamar, Bharat S. Chaudhari, Ronald Criollo, David Cuartielles, José A. Ferreira Filho, Solomon Gizaw, Evgeni Gousev, Alessandro Grande, Shawn Hymel, Peter Ing, Prashant Manandhar, Pietro Manzoni, Boris Murmann, Eric Pan, Rytis Paskauskas, Ermanno Pietrosemoli, Tales C. Pimenta, Marcelo Rovai, Marco Zennaro, Vijay Janapa Reddi:
TinyML4D: Scaling Embedded Machine Learning Education in the Developing World. AAAI Spring Symposia 2024: 508-515 - [c137]Jonas Crols, Guilherme Paim, Shirui Zhao, Marian Verhelst:
TreeGRNG: Binary Tree Gaussian Random Number Generator for Efficient Probabilistic AI Hardware. DATE 2024: 1-6 - [c136]Man Shi, Vikram Jain, Antony Joseph, Maurice Meijer, Marian Verhelst:
BitWave: Exploiting Column-Based Bit-Level Sparsity for Deep Learning Acceleration. HPCA 2024: 732-746 - [c135]Joren Dumoulin, Pouya Houshmand, Vikram Jain, Marian Verhelst:
Enabling Efficient Hardware Acceleration of Hybrid Vision Transformer (ViT) Networks at the Edge. ISCAS 2024: 1-5 - [c134]Steven Colleman, Arne Symons, Victor J. B. Jung, Marian Verhelst:
Optimizing Layer-Fused Scheduling of Transformer Networks on Multi-accelerator Platforms. ISQED 2024: 1-6 - [c133]Pouya Houshmand, Jean-Sebastien Staelens, Ward van der Tempel, Marian Verhelst:
High-Rate. Compact In-Sensor Denoising for Active Stereo Vision Towards Embedded Depth Sensing. NewCAS 2024: 11-15 - [c132]Robin Geens, Man Shi, Arne Symons, Chao Fang, Marian Verhelst:
Energy Cost Modelling for Optimizing Large Language Model Inference on Hardware Accelerators. SOCC 2024: 1-6 - [c131]Nitish Satya Murthy, Nathan Laubeuf, Debjyoti Bhattacharjee, Francky Catthoor, Marian Verhelst:
Adaptive Block-Scaled GeMMs on Vector Processors for DNN Training at the Edge. VLSI-SoC 2024: 1-6 - [i37]Jiacong Sun, Pouya Houshmand, Marian Verhelst:
Analog or Digital In-memory Computing? Benchmarking through Quantitative Modeling. CoRR abs/2405.14978 (2024) - [i36]Josse Van Delm, Maarten Vandersteegen, Alessio Burrello, Giuseppe Maria Sarda, Francesco Conti, Daniele Jahier Pagliari, Luca Benini, Marian Verhelst:
HTVM: Efficient Neural Network Deployment On Heterogeneous TinyML Platforms. CoRR abs/2406.07453 (2024) - [i35]Steven Colleman, Arne Symons, Victor J. B. Jung, Marian Verhelst:
Optimizing Layer-Fused Scheduling of Transformer Networks on Multi-accelerator Platforms. CoRR abs/2406.09804 (2024) - [i34]Steven Colleman, Man Shi, Marian Verhelst:
COAC: Cross-layer Optimization of Accelerator Configurability for Efficient CNN Processing. CoRR abs/2406.13752 (2024) - [i33]Man Shi, Steven Colleman, Charlotte VanDeMieroop, Antony Joseph, Maurice Meijer, Wim Dehaene, Marian Verhelst:
CMDS: Cross-layer Dataflow Optimization for DNN Accelerators Exploiting Multi-bank Memories. CoRR abs/2406.14574 (2024) - [i32]Giuseppe Maria Sarda, Nimish Shah, Debjyoti Bhattacharjee, Peter Debacker, Marian Verhelst:
Optimising GPGPU Execution Through Runtime Micro-Architecture Parameter Analysis. CoRR abs/2407.11999 (2024) - [i31]Pouya Houshmand, Marian Verhelst:
Pack my weights and run! Minimizing overheads for in-memory computing accelerators. CoRR abs/2409.11437 (2024) - [i30]Mohamed Amine Hamdi, Francesco Daghero, Giuseppe Maria Sarda, Josse Van Delm, Arne Symons, Luca Benini, Marian Verhelst, Daniele Jahier Pagliari, Alessio Burrello:
MATCH: Model-Aware TVM-based Compilation for Heterogeneous Edge Devices. CoRR abs/2410.08855 (2024) - [i29]Xiaoling Yi, Ryan Antonio, Joren Dumoulin, Jiacong Sun, Josse Van Delm, Guilherme Paim, Marian Verhelst:
OpenGeMM: A High-Utilization GeMM Accelerator Generator with Lightweight RISC-V Control and Tight Memory Coupling. CoRR abs/2411.09543 (2024) - [i28]Chao Fang, Man Shi, Robin Geens, Arne Symons, Zhongfeng Wang, Marian Verhelst:
Anda: Unlocking Efficient LLM Inference with a Variable-Length Grouped Activation Data Format. CoRR abs/2411.15982 (2024) - 2023
- [j65]Pouya Houshmand, Giuseppe Maria Sarda, Vikram Jain, Kodai Ueyoshi, Ioannis A. Papistas, Man Shi, Qilin Zheng, Debjyoti Bhattacharjee, Arindam Mallik, Peter Debacker, Diederik Verkest, Marian Verhelst:
DIANA: An End-to-End Hybrid DIgital and ANAlog Neural Network SoC for the Edge. IEEE J. Solid State Circuits 58(1): 203-215 (2023) - [j64]Koen Goetschalckx, Fengfeng Wu, Marian Verhelst:
DepFiN: A 12-nm Depth-First, High-Resolution CNN Processor for IO-Efficient Inference. IEEE J. Solid State Circuits 58(5): 1425-1435 (2023) - [j63]Vikram Jain, Juan Sebastian Piedrahita Giraldo, Jaro De Roose, Linyan Mei, Bert Boons, Marian Verhelst:
TinyVers: A Tiny Versatile System-on-Chip With State-Retentive eMRAM for ML Inference at the Extreme Edge. IEEE J. Solid State Circuits 58(8): 2360-2371 (2023) - [j62]Yingping Chen, Bernardo Tacca, Yunzhu Chen, Dwaipayan Biswas, Georges G. E. Gielen, Francky Catthoor, Marian Verhelst, Carolina Mora Lopez:
An Online-Spike-Sorting IC Using Unsupervised Geometry-Aware OSort Clustering for Efficient Embedded Neural-Signal Processing. IEEE J. Solid State Circuits 58(11): 2990-3002 (2023) - [j61]Thomas Bos, Marian Verhelst, Wim Dehaene:
An End-to-End Dual ASIC OFDM Transceiver for Ultrasound In-Body Communication. IEEE Trans. Biomed. Circuits Syst. 17(4): 664-673 (2023) - [j60]Peishuo Li, Tom R. Molderez, David H. Villamor, Antonin Prévoteau, Marian Verhelst:
A 96-Channel 40nm CMOS Potentiostat for Parallel Experiments on Microbial Electrochemical Systems. IEEE Trans. Circuits Syst. I Regul. Pap. 70(1): 114-127 (2023) - [j59]Jun Yin, Marian Verhelst:
CNN-based Robust Sound Source Localization with SRP-PHAT for the Extreme Edge. ACM Trans. Embed. Comput. Syst. 22(3): 55:1-55:27 (2023) - [j58]Steven Colleman, Man Shi, Marian Verhelst:
COAC: Cross-Layer Optimization of Accelerator Configurability for Efficient CNN Processing. IEEE Trans. Very Large Scale Integr. Syst. 31(7): 945-958 (2023) - [c130]Victor J. B. Jung, Arne Symons, Linyan Mei, Marian Verhelst, Luca Benini:
SALSA: Simulated Annealing based Loop-Ordering Scheduler for DNN Accelerators. AICAS 2023: 1-5 - [c129]Lotte Hendrickx, Arne Symons, Wiebe Van Ranst, Marian Verhelst, Toon Goedemé:
Hardware-aware NAS by Genetic Optimisation with a Design Space Exploration Simulator. CVPR Workshops 2023: 2275-2283 - [c128]Josse Van Delm, Maarten Vandersteegen, Alessio Burrello, Giuseppe Maria Sarda, Francesco Conti, Daniele Jahier Pagliari, Luca Benini, Marian Verhelst:
HTVM: Efficient Neural Network Deployment On Heterogeneous TinyML Platforms. DAC 2023: 1-6 - [c127]Vikram Jain, Matheus A. Cavalcante, Nazareno Bruschi, Michael Rogenmoser, Thomas Benz, Andreas Kurth, Davide Rossi, Luca Benini, Marian Verhelst:
PATRONoC: Parallel AXI Transport Reducing Overhead for Networks-on-Chip targeting Multi-Accelerator DNN Platforms at the Edge. DAC 2023: 1-6 - [c126]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 K. Gürkaynak, 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 Güneysu, Henk Corporaal:
PetaOps/W edge-AI $\mu$ Processors: Myth or reality? DATE 2023: 1-6 - [c125]Sebastian Karl, Arne Symons, Nael Fasfous, Marian Verhelst:
Genetic Algorithm-based Framework for Layer-Fused Scheduling of Multiple DNNs on Multi-core Systems. DATE 2023: 1-6 - [c124]Jun Yin, Stefano Damiano, Marian Verhelst, Toon van Waterschoot, Andre Guntoro:
Real-Time Acoustic Perception for Automotive Applications. DATE 2023: 1-6 - [c123]Weijie Jiang, Pouya Houshmand, Marian Verhelst, Wim Dehaene:
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. ESSCIRC 2023: 409-412 - [c122]Linyan Mei, Koen Goetschalckx, Arne Symons, Marian Verhelst:
DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling. HPCA 2023: 570-583 - [c121]Jiacong Sun, Pouya Houshmand, Marian Verhelst:
Analog or Digital In-Memory Computing? Benchmarking Through Quantitative Modeling. ICCAD 2023: 1-9 - [c120]Jun Yin, Linyan Mei, Andre Guntoro, Marian Verhelst:
ACCO: Automated Causal CNN Scheduling Optimizer for Real-Time Edge Accelerators. ICCD 2023: 391-398 - [c119]Giuseppe Maria Sarda, Nimish Shah, Debjyoti Bhattacharjee, Peter Debacker, Marian Verhelst:
Optimising GPGPU Execution Through Runtime Micro-Architecture Parameter Analysis. IISWC 2023: 226-228 - [c118]Matteo Risso, Alessio Burrello, Giuseppe Maria Sarda, Luca Benini, Enrico Macii, Massimo Poncino, Marian Verhelst, Daniele Jahier Pagliari:
Precision-aware Latency and Energy Balancing on Multi-Accelerator Platforms for DNN Inference. ISLPED 2023: 1-6 - [c117]Arne Symons, Linyan Mei, Steven Colleman, Pouya Houshmand, Sebastian Karl, Marian Verhelst:
Stream: A Modeling Framework for Fine-grained Layer Fusion on Multi-core DNN Accelerators. ISPASS 2023: 355-357 - [c116]Man Shi, Steven Colleman, Charlotte VanDeMieroop, Antony Joseph, Maurice Meijer, Wim Dehaene, Marian Verhelst:
CMDS: Cross-layer Dataflow Optimization for DNN Accelerators Exploiting Multi-bank Memories. ISQED 2023: 1-8 - [c115]Yingping Chen, Bernardo Tacca, Yunzhu Chen, Dwaipayan Biswas, Georges G. E. Gielen, Francky Catthoor, Marian Verhelst, Carolina Mora Lopez:
A 384-Channel Online-Spike-Sorting IC Using Unsupervised Geo-OSort Clustering and Achieving 0.0013mm2/Ch and $1.78\mu \text{W/ch}$. ISSCC 2023: 486-487 - [c114]Nitish Satya Murthy, Francky Catthoor, Marian Verhelst, Peter Vrancx:
Quantized Dynamics Models for Hardware-Efficient Control and Planning in Model-Based RL. PKDD/ECML Workshops (5) 2023: 196-209 - [i27]Vikram Jain, Juan Sebastian Piedrahita Giraldo, Jaro De Roose, Linyan Mei, Bert Boons, Marian Verhelst:
TinyVers: A Tiny Versatile System-on-chip with State-Retentive eMRAM for ML Inference at the Extreme Edge. CoRR abs/2301.03537 (2023) - [i26]Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sander M. Bohté, Younes Bouhadjar, Sonia M. Buckley, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Reddy Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Jeremy Forest, Steve B. Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos P. Michmizos, Dylan R. Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayça Özcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Pao-Sheng Sun, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Catherine D. Schuman, Jae-sun Seo, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Michael Stewart, Terrence C. Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi:
NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. CoRR abs/2304.04640 (2023) - [i25]Victor J. B. Jung, Arne Symons, Linyan Mei, Marian Verhelst, Luca Benini:
SALSA: Simulated Annealing based Loop-Ordering Scheduler for DNN Accelerators. CoRR abs/2304.12931 (2023) - [i24]Pouya Houshmand, Jiacong Sun, Marian Verhelst:
Benchmarking and modeling of analog and digital SRAM in-memory computing architectures. CoRR abs/2305.18335 (2023) - [i23]Matteo Risso, Alessio Burrello, Giuseppe Maria Sarda, Luca Benini, Enrico Macii, Massimo Poncino, Marian Verhelst, Daniele Jahier Pagliari:
Precision-aware Latency and Energy Balancing on Multi-Accelerator Platforms for DNN Inference. CoRR abs/2306.05060 (2023) - [i22]Vikram Jain, Matheus A. Cavalcante, Nazareno Bruschi, Michael Rogenmoser, Thomas Benz, Andreas Kurth, Davide Rossi, Luca Benini, Marian Verhelst:
PATRONoC: Parallel AXI Transport Reducing Overhead for Networks-on-Chip targeting Multi-Accelerator DNN Platforms at the Edge. CoRR abs/2308.00154 (2023) - 2022
- [j57]Geoffrey W. Burr, Sukhwan Lim, Boris Murmann, Rangharajan Venkatesan, Marian Verhelst:
Fair and Comprehensive Benchmarking of Machine Learning Processing Chips. IEEE Des. Test 39(3): 18-27 (2022) - [j56]Vikram Jain, Ninad Jadhav, Marian Verhelst:
Enabling real-time object detection on low cost FPGAs. J. Real Time Image Process. 19(1): 217-229 (2022) - [j55]Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst:
DPU: DAG Processing Unit for Irregular Graphs With Precision-Scalable Posit Arithmetic in 28 nm. IEEE J. Solid State Circuits 57(8): 2586-2596 (2022) - [j54]Ehab M. Ibrahim, Linyan Mei, Marian Verhelst:
Taxonomy and Benchmarking of Precision-Scalable MAC Arrays Under Enhanced DNN Dataflow Representation. IEEE Trans. Circuits Syst. I Regul. Pap. 69(5): 2013-2024 (2022) - [j53]Nimish Shah, Wannes Meert, Marian Verhelst:
GraphOpt: Constrained-Optimization-Based Parallelization of Irregular Graphs. IEEE Trans. Parallel Distributed Syst. 33(12): 3321-3332 (2022) - [c113]Steven Colleman, Peter Zhu, Wei Sun, Marian Verhelst:
Optimizing Accelerator Configurability for Mobile Transformer Networks. AICAS 2022: 142-145 - [c112]Thomas Bos, Marian Verhelst, Wim Dehaene:
A Flexible End-to-End Dual ASIC Transceiver for OFDM Ultrasound In-Body Communication. BioCAS 2022: 21-25 - [c111]Linyan Mei, Huichu Liu, Tony F. Wu, Huseyin Ekin Sumbul, Marian Verhelst, Edith Beigné:
A Uniform Latency Model for DNN Accelerators with Diverse Architectures and Dataflows. DATE 2022: 220-225 - [c110]Shirui Zhao, Nimish Shah, Wannes Meert, Marian Verhelst:
Discrete Samplers for Approximate Inference in Probabilistic Machine Learning. DATE 2022: 1221-1226 - [c109]Nitish Satya Murthy, Peter Vrancx, Nathan Laubeuf, Peter Debacker, Francky Catthoor, Marian Verhelst:
Learn to Learn on Chip: Hardware-aware Meta-learning for Quantized Few-shot Learning at the Edge. SEC 2022: 14-25 - [c108]Kodai Ueyoshi, Ioannis A. Papistas, Pouya Houshmand, Giuseppe Maria Sarda, Vikram Jain, Man Shi, Qilin Zheng, Juan Sebastian Piedrahita Giraldo, Peter Vrancx, Jonas Doevenspeck, Debjyoti Bhattacharjee, Stefan Cosemans, Arindam Mallik, Peter Debacker, Diederik Verkest, Marian Verhelst:
DIANA: An End-to-End Energy-Efficient Digital and ANAlog Hybrid Neural Network SoC. ISSCC 2022: 1-3 - [c107]Nimish Shah, Wannes Meert, Marian Verhelst:
DPU-v2: Energy-efficient execution of irregular directed acyclic graphs. MICRO 2022: 1288-1307 - [c106]Vikram Jain, Juan Sebastian Piedrahita Giraldo, Jaro De Roose, Bert Boons, Linyan Mei, Marian Verhelst:
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. VLSI Technology and Circuits 2022: 20-21 - [d1]Linyan Mei, Koen Goetschalckx, Arne Symons, Marian Verhelst:
DeFiNES: A DSE Framework Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators. Zenodo, 2022
- [i21]Zuzana Jelcicová, Marian Verhelst:
Delta Keyword Transformer: Bringing Transformers to the Edge through Dynamically Pruned Multi-Head Self-Attention. CoRR abs/2204.03479 (2022) - [i20]Maxim Bonnaerens, Matthias Freiberger, Marian Verhelst, Joni Dambre:
Hardware-aware mobile building block evaluation for computer vision. CoRR abs/2208.12694 (2022) - [i19]Nimish Shah, Wannes Meert, Marian Verhelst:
DPU-v2: Energy-efficient execution of irregular directed acyclic graphs. CoRR abs/2210.13184 (2022) - [i18]Manil Dev Gomony, Floran de Putter, Anteneh Gebregiorgis, Gianna Paulin, Linyan Mei, Vikram Jain, Said Hamdioui, Victor Sanchez, Tobias Grosser, Marc Geilen, Marian Verhelst, Frank K. Zenke, Frank K. Gürkaynak, Barry de Bruin, Sander Stuijk, Simon Davidson, Sayandip De, Mounir Ghogho, Alexandra Jimborean, Sherif Eissa, Luca Benini, Dimitrios Soudris, Rajendra Bishnoi, S. Ainsworth, Federico Corradi, Ouassim Karrakchou, Tim Güneysu, Henk Corporaal:
CONVOLVE: Smart and seamless design of smart edge processors. CoRR abs/2212.00873 (2022) - [i17]Linyan Mei, Koen Goetschalckx, Arne Symons, Marian Verhelst:
DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling. CoRR abs/2212.05344 (2022) - [i16]Arne Symons, Linyan Mei, Steven Colleman, Pouya Houshmand, Sebastian Karl, Marian Verhelst:
Towards Heterogeneous Multi-core Accelerators Exploiting Fine-grained Scheduling of Layer-Fused Deep Neural Networks. CoRR abs/2212.10612 (2022) - 2021
- [j52]Tom Vermeulen, Brecht Reynders, Fernando E. Rosas, Marian Verhelst, Sofie Pollin:
Performance analysis of in-band collision detection for dense wireless networks. EURASIP J. Wirel. Commun. Netw. 2021(1): 87 (2021) - [j51]Man Shi, Pouya Houshmand, Linyan Mei, Marian Verhelst:
Hardware-Efficient Residual Neural Network Execution in Line-Buffer Depth-First Processing. IEEE J. Emerg. Sel. Topics Circuits Syst. 11(4): 690-700 (2021) - [j50]Linyan Mei, Pouya Houshmand, Vikram Jain, Juan Sebastian Piedrahita Giraldo, Marian Verhelst:
ZigZag: Enlarging Joint Architecture-Mapping Design Space Exploration for DNN Accelerators. IEEE Trans. Computers 70(8): 1160-1174 (2021) - [j49]Tom R. Molderez, Korneel Rabaey, Marian Verhelst:
A Scalable 128-Channel, Time-Multiplexed Potentiostat for Parallel Electrochemical Experiments. IEEE Trans. Circuits Syst. I Regul. Pap. 68(3): 1068-1079 (2021) - [j48]Juan Sebastian Piedrahita Giraldo, Marian Verhelst:
Hardware Acceleration for Embedded Keyword Spotting: Tutorial and Survey. ACM Trans. Embed. Comput. Syst. 20(6): 111:1-111:25 (2021) - [j47]Steven Colleman, Marian Verhelst:
High-Utilization, High-Flexibility Depth-First CNN Coprocessor for Image Pixel Processing on FPGA. IEEE Trans. Very Large Scale Integr. Syst. 29(3): 461-471 (2021) - [j46]Juan Sebastian Piedrahita Giraldo, Vikram Jain, Marian Verhelst:
Efficient Execution of Temporal Convolutional Networks for Embedded Keyword Spotting. IEEE Trans. Very Large Scale Integr. Syst. 29(12): 2220-2228 (2021) - [c105]Vikram Jain, Linyan Mei, Marian Verhelst:
Analyzing the Energy-Latency-Area-Accuracy Trade-off Across Contemporary Neural Networks. AICAS 2021: 1-4 - [c104]Arne Symons, Linyan Mei, Marian Verhelst:
LOMA: Fast Auto-Scheduling on DNN Accelerators through Loop-Order-based Memory Allocation. AICAS 2021: 1-4 - [c103]Peishuo Li, Tom R. Molderez, Marian Verhelst:
A 96-channel 40nm CMOS Fully-Integrated Potentiostat for Electrochemical Monitoring. ESSCIRC 2021: 167-170 - [c102]Peishuo Li, Tom R. Molderez, Marian Verhelst:
A 96-channel 40nm CMOS Fully-Integrated Potentiostat for Electrochemical Monitoring. ESSDERC 2021: 167-170 - [c101]Zuzana Jelcicová, Rasmus Jones, David Thorn Blix, Marian Verhelst, Jens Sparsø:
PeakRNN and StatsRNN: Dynamic Pruning in Recurrent Neural Networks. EUSIPCO 2021: 416-420 - [c100]Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst:
9.4 PIU: A 248GOPS/W Stream-Based Processor for Irregular Probabilistic Inference Networks Using Precision-Scalable Posit Arithmetic in 28nm. ISSCC 2021: 150-152 - [c99]Steven Colleman, Thomas Verelst, Linyan Mei, Tinne Tuytelaars, Marian Verhelst:
Processor Architecture Optimization for Spatially Dynamic Neural Networks. VLSI-SoC 2021: 1-6 - [c98]Koen Goetschalckx, Marian Verhelst:
DepFiN: A 12nm, 3.8TOPs depth-first CNN processor for high res. image processing. VLSI Circuits 2021: 1-2 - [i15]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
ProbLP: A framework for low-precision probabilistic inference. CoRR abs/2103.00216 (2021) - [i14]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
Acceleration of probabilistic reasoning through custom processor architecture. CoRR abs/2103.00266 (2021) - [i13]Nimish Shah, Wannes Meert, Marian Verhelst:
GRAPHOPT: constrained optimization-based parallelization of irregular graphs. CoRR abs/2105.01976 (2021) - [i12]Ehab M. Ibrahim, Linyan Mei, Marian Verhelst:
Survey and Benchmarking of Precision-Scalable MAC Arrays for Embedded DNN Processing. CoRR abs/2108.04773 (2021) - [i11]Nimish Shah, Laura Isabel Galindez Olascoaga, Shirui Zhao, Wannes Meert, Marian Verhelst:
DPU: DAG Processing Unit for Irregular Graphs with Precision-Scalable Posit Arithmetic in 28nm. CoRR abs/2112.05660 (2021) - 2020
- [j45]Juan Sebastian Piedrahita Giraldo, Steven Lauwereins, Komail M. H. Badami, Marian Verhelst:
Vocell: A 65-nm Speech-Triggered Wake-Up SoC for 10- $\mu$ W Keyword Spotting and Speaker Verification. IEEE J. Solid State Circuits 55(4): 868-878 (2020) - [j44]Athanasios T. Ramkaj, Juan Carlos Pena Ramos, Marcel J. M. Pelgrom, Michiel S. J. Steyaert, Marian Verhelst, Filip Tavernier:
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. IEEE J. Solid State Circuits 55(6): 1553-1564 (2020) - [j43]Fernando de la Hucha Arce, Marc Moonen, Marian Verhelst, Alexander Bertrand:
Distributed adaptive node-specific signal estimation in a wireless sensor network with noisy links. Signal Process. 166 (2020) - [j42]Fernando de la Hucha Arce, Panagiotis Patrinos, Marian Verhelst, Alexander Bertrand:
On the Convexity of Bit Depth Allocation for Linear MMSE Estimation in Wireless Sensor Networks. IEEE Signal Process. Lett. 27: 291-295 (2020) - [j41]Leandro Mateus Giacomini Rocha, Dwaipayan Biswas, Bram-Ernst Verhoef, Sergio Bampi, Chris Van Hoof, Mario Konijnenburg, Marian Verhelst, Nick Van Helleputte:
Binary CorNET: Accelerator for HR Estimation From Wrist-PPG. IEEE Trans. Biomed. Circuits Syst. 14(4): 715-726 (2020) - [c97]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
Acceleration of probabilistic reasoning through custom processor architecture. DATE 2020: 322-325 - [c96]Robby Neven, Marian Verhelst, Tinne Tuytelaars, Toon Goedemé:
Feed-Forward On-Edge Fine-Tuning Using Static Synthetic Gradient Modules. ECCV Workshops (5) 2020: 131-146 - [c95]Tom R. Molderez, Korneel Rabaey, Marian Verhelst:
An Affordable Multichannel Potentiostat with 128 Individual Stimulation and Sensing Channels. I2MTC 2020: 1-6 - [c94]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst:
Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams. IDA 2020: 184-196 - [c93]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst:
Dynamic Complexity Tuning for Hardware-Aware Probabilistic Circuits. IoT Streams/ITEM@PKDD/ECML 2020: 283-295 - [i10]Colby R. Banbury, Vijay Janapa Reddi, Max Lam, William Fu, Amin Fazel, Jeremy Holleman, Xinyuan Huang, Robert Hurtado, David Kanter, Anton Lokhmotov, David A. Patterson, Danilo Pau, Jae-sun Seo, Jeff Sieracki, Urmish Thakker, Marian Verhelst, Poonam Yadav:
Benchmarking TinyML Systems: Challenges and Direction. CoRR abs/2003.04821 (2020) - [i9]Linyan Mei, Pouya Houshmand, Vikram Jain, Juan Sebastian Piedrahita Giraldo, Marian Verhelst:
ZigZag: A Memory-Centric Rapid DNN Accelerator Design Space Exploration Framework. CoRR abs/2007.11360 (2020) - [i8]Robby Neven, Marian Verhelst, Tinne Tuytelaars, Toon Goedemé:
Feed-Forward On-Edge Fine-tuning Using Static Synthetic Gradient Modules. CoRR abs/2009.09675 (2020)
2010 – 2019
- 2019
- [j40]Koen Goetschalckx, Marian Verhelst:
Breaking High-Resolution CNN Bandwidth Barriers With Enhanced Depth-First Execution. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(2): 323-331 (2019) - [j39]Vincent Camus, Linyan Mei, Christian C. Enz, Marian Verhelst:
Review and Benchmarking of Precision-Scalable Multiply-Accumulate Unit Architectures for Embedded Neural-Network Processing. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(4): 697-711 (2019) - [j38]Daniel Bankman, Lita Yang, Bert Moons, Marian Verhelst, Boris Murmann:
An Always-On 3.8 $\mu$ J/86% CIFAR-10 Mixed-Signal Binary CNN Processor With All Memory on Chip in 28-nm CMOS. IEEE J. Solid State Circuits 54(1): 158-172 (2019) - [j37]Thomas Bos, Wentao Jiang, Jan D'hooge, Marian Verhelst, Wim Dehaene:
Enabling Ultrasound In-Body Communication: FIR Channel Models and QAM Experiments. IEEE Trans. Biomed. Circuits Syst. 13(1): 135-144 (2019) - [j36]Tom R. Molderez, Xu Zhang, Korneel Rabaey, Marian Verhelst:
A Current-Driven Six-Channel Potentiostat for Rapid Performance Characterization of Microbial Electrolysis Cells. IEEE Trans. Instrum. Meas. 68(12): 4694-4702 (2019) - [j35]Massimo Alioto, Magdy S. Abadir, Tughrul Arslan, Chirn Chye Boon, Andreas Burg, Chip-Hong Chang, Meng-Fan Chang, Yao-Wen Chang, Poki Chen, Pasquale Corsonello, Paolo Crovetti, Shiro Dosho, Rolf Drechsler, Ibrahim Abe M. Elfadel, Ruonan Han, Masanori Hashimoto, Chun-Huat Heng, Deukhyoun Heo, Tsung-Yi Ho, Houman Homayoun, Yuh-Shyan Hwang, Ajay Joshi, Rajiv V. Joshi, Tanay Karnik, Chulwoo Kim, Tony Tae-Hyoung Kim, Jaydeep Kulkarni, Volkan Kursun, Yoonmyung Lee, Hai Helen Li, Huawei Li, Prabhat Mishra, Baker Mohammad, Mehran Mozaffari Kermani, Makoto Nagata, Koji Nii, Partha Pratim Pande, Bipul C. Paul, Vasilis F. Pavlidis, José Pineda de Gyvez, Ioannis Savidis, Patrick Schaumont, Fabio Sebastiano, Anirban Sengupta, Mingoo Seok, Mircea R. Stan, Mark M. Tehranipoor, Aida Todri-Sanial, Marian Verhelst, Valerio Vignoli, Xiaoqing Wen, Jiang Xu, Wei Zhang, Zhengya Zhang, Jun Zhou, Mark Zwolinski, Stacey Weber:
Editorial TVLSI Positioning - Continuing and Accelerating an Upward Trajectory. IEEE Trans. Very Large Scale Integr. Syst. 27(2): 253-280 (2019) - [c92]Linyan Mei, Mohit Dandekar, Dimitrios Rodopoulos, Jeremy Constantin, Peter Debacker, Rudy Lauwereins, Marian Verhelst:
Sub-Word Parallel Precision-Scalable MAC Engines for Efficient Embedded DNN Inference. AICAS 2019: 6-10 - [c91]Vincent Camus, Christian C. Enz, Marian Verhelst:
Survey of Precision-Scalable Multiply-Accumulate Units for Neural-Network Processing. AICAS 2019: 57-61 - [c90]Juan Sebastian Piedrahita Giraldo, Chris O'Connor, Marian Verhelst:
Efficient Keyword Spotting through Hardware-Aware Conditional Execution of Deep Neural Networks. AICCSA 2019: 1-8 - [c89]Thomas Bos, Wim Dehaene, Marian Verhelst:
Ultrasound In-Body Communication with OFDM through Multipath Realistic Channels. BioCAS 2019: 1-4 - [c88]Leandro Mateus Giacomini Rocha, Nick Van Helleputte, Muqing Liu, Dwaipayan Biswas, Bram-Ernst Verhoef, Sergio Bampi, Chris H. Kim, Chris Van Hoof, Mario Konijnenburg, Marian Verhelst:
Real-time HR Estimation from wrist PPG using Binary LSTMs. BioCAS 2019: 1-4 - [c87]Parvez Ahmmed, James Dieffenderfer, Jose Manuel Valero-Sarmiento, Venkata Rajesh Pamula, Nick Van Helleputte, Chris Van Hoof, Marian Verhelst, Alper Bozkurt:
A Wearable Wrist-Band with Compressive Sensing based Ultra-Low Power Photoplethysmography Readout Circuit. BSN 2019: 1-4 - [c86]Nimish Shah, Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst:
ProbLP: A framework for low-precision probabilistic inference. DAC 2019: 190 - [c85]Maxime Feyerick, Jaro De Roose, Marian Verhelst:
Exploration and Design of Low-Energy Logic Cells for 1 kHz Always-on Systems. DATE 2019: 1697-1702 - [c84]Peishuo Li, Tom R. Molderez, Frederik Ceyssens, Korneel Rabaey, Marian Verhelst:
A 64-channel, 1.1-pA-accurate On-chip Potentiostat for Parallel Electrochemical Monitoring. ESSCIRC 2019: 317-320 - [c83]Sander Smets, Toon Goedemé, Anurag Mittal, Marian Verhelst:
A 978GOPS/W Flexible Streaming Processor for Real-Time Image Processing Applications in 22nm FDSOI. ISSCC 2019: 44-46 - [c82]Athanasios Ramkaj, Juan Carlos Pena Ramos, Yifan Lyu, Maarten Strackx, Marcel J. M. Pelgrom, Michiel Steyaert, Marian Verhelst, Filip Tavernier:
A 5GS/s 158.6mW 12b Passive-Sampling 8×-Interleaved Hybrid ADC with 9.4 ENOB and 160.5dB FoMS in 28nm CMOS. ISSCC 2019: 62-64 - [c81]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Guy Van den Broeck, Marian Verhelst:
On Hardware-Aware Probabilistic Frameworks for Resource Constrained Embedded Applications. EMC2@NeurIPS 2019: 66-70 - [c80]Laura Isabel Galindez Olascoaga, Wannes Meert, Nimish Shah, Marian Verhelst, Guy Van den Broeck:
Towards Hardware-Aware Tractable Learning of Probabilistic Models. NeurIPS 2019: 13726-13736 - [c79]Juan Sebastian Piedrahita Giraldo, Steven Lauwereins, Komail M. H. Badami, Hugo Van hamme, Marian Verhelst:
18μW SoC for near-microphone Keyword Spotting and Speaker Verification. VLSI Circuits 2019: 52- - 2018
- [j34]Laura Isabel Galindez Olascoaga, Komail M. H. Badami, Jonas Vlasselaer, Wannes Meert, Marian Verhelst:
Dynamic Sensor-Frontend Tuning for Resource Efficient Embedded Classification. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(4): 858-872 (2018) - [j33]Koen Goetschalckx, Bert Moons, Steven Lauwereins, Martin Andraud, Marian Verhelst:
Optimized Hierarchical Cascaded Processing. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(4): 884-894 (2018) - [j32]Juan Carlos Pena Ramos, Komail M. H. Badami, Steven Lauwereins, Marian Verhelst:
A Fully Configurable Non-Linear Mixed-Signal Interface for Multi-Sensor Analytics. IEEE J. Solid State Circuits 53(11): 3140-3149 (2018) - [j31]Chunshu Li, Yanxiang Huang, Khaled Khalaf, André Bourdoux, Marian Verhelst, Liesbet Van der Perre, Sofie Pollin:
Energy-Efficient Digital Front-End Processor for 60 GHz Polar Transmitter. J. Signal Process. Syst. 90(5): 777-789 (2018) - [c78]Bert Moons, Daniel Bankman, Lita Yang, Boris Murmann, Marian Verhelst:
BinarEye: An always-on energy-accuracy-scalable binary CNN processor with all memory on chip in 28nm CMOS. CICC 2018: 1-4 - [c77]Gage Hills, Daniel Bankman, Bert Moons, Lita Yang, Jake Hillard, Alex Kahng, Rebecca Park, Marian Verhelst, Boris Murmann, Max M. Shulaker, H.-S. Philip Wong, Subhasish Mitra:
TRIG: hardware accelerator for inference-based applications and experimental demonstration using carbon nanotube FETs. DAC 2018: 74:1-74:10 - [c76]Laura Isabel Galindez Olascoaga, Jonas Vlasselaer, Wannes Meert, Marian Verhelst:
Feature noise tuning for resource efficient Bayesian Network Classifiers. ESANN 2018 - [c75]Juan Sebastian Piedrahita Giraldo, Marian Verhelst:
Laika: A 5uW Programmable LSTM Accelerator for Always-on Keyword Spotting in 65nm CMOS. ESSCIRC 2018: 166-169 - [c74]Marian Verhelst:
Exploiting FDSOI Towards Minimum Energy Point Operation in Processors and Machine Learning Accelerators. ESSCIRC 2018: 217 - [c73]Jaro De Roose, Haoming Xin, Martin Andraud, Pieter J. A. Harpe, Marian Verhelst:
Flexible and Self-Adaptive Sense-and-Compress for Sub-MicroWatt Always-on Sensory Recording. ESSCIRC 2018: 282-285 - [c72]Marian Verhelst:
Exploiting FDSOI towards minimum energy point operation in processors and machine learning accelerators. ESSDERC 2018: 157 - [c71]Martin Andraud, Ahmed Hallawa, Jaro De Roose, Eugenio Cantatore, Gerd Ascheid, Marian Verhelst:
Evolving hardware instinctive behaviors in resource-scarce agent swarms exploring hard-to-reach environments. GECCO (Companion) 2018: 1497-1504 - [c70]Martin Andraud, Marian Verhelst:
From on-chip self-healing to self-adaptivity in analog/RF ICs: challenges and opportunities. IOLTS 2018: 131-134 - [c69]Lita Yang, Daniel Bankman, Bert Moons, Marian Verhelst, Boris Murmann:
Bit Error Tolerance of a CIFAR-10 Binarized Convolutional Neural Network Processor. ISCAS 2018: 1-5 - [c68]Daniel Bankman, Lita Yang, Bert Moons, Marian Verhelst, Boris Murmann:
An always-on 3.8μJ/86% CIFAR-10 mixed-signal binary CNN processor with all memory on chip in 28nm CMOS. ISSCC 2018: 222-224 - [c67]Komail M. H. Badami, Juan Carlos Pena Ramos, Steven Lauwereins, Marian Verhelst:
Mixed-signal programmable non-linear interface for resource-efficient multi-sensor analytics. ISSCC 2018: 344-346 - [c66]Martin Andraud, Laura Isabel Galindez Olascoaga, Yichuan Lu, Yiorgos Makris, Marian Verhelst:
On the use of Bayesian Networks for Resource-Efficient Self-Calibration of Analog/RF ICs. ITC 2018: 1-10 - [c65]Koen Goetschalckx, Bert Moons, Patrick Wambacq, Marian Verhelst:
Efficiently Combining SVD, Pruning, Clustering and Retraining for Enhanced Neural Network Compression. EMDL@MobiSys 2018: 1-6 - [c64]Jonas Vlasselaer, Wannes Meert, Marian Verhelst:
Towards Resource-Efficient Classifiers for Always-On Monitoring. ECML/PKDD (3) 2018: 305-321 - [c63]Komail M. H. Badami, Kushal Dakshina Murthy, Pieter Harpe, Marian Verhelst:
A 0.6V 54DB SNR Analog Frontend with 0.18% THD for Low Power Sensory Applications in 65NM CMOS. VLSI Circuits 2018: 241-242 - [i7]Matthijs Van Keirsbilck, Bert Moons, Marian Verhelst:
Resource aware design of a deep convolutional-recurrent neural network for speech recognition through audio-visual sensor fusion. CoRR abs/1803.04840 (2018) - [i6]Bert Moons, Daniel Bankman, Lita Yang, Boris Murmann, Marian Verhelst:
BinarEye: An Always-On Energy-Accuracy-Scalable Binary CNN Processor With All Memory On Chip in 28nm CMOS. CoRR abs/1804.05554 (2018) - [i5]Gert Dekkers, Fernando Rosas, Steven Lauwereins, Sreeraj Rajendran, Sofie Pollin, Bart Vanrumste, Toon van Waterschoot, Marian Verhelst, Peter Karsmakers:
A multi-layered energy consumption model for smart wireless acoustic sensor networks. CoRR abs/1812.06672 (2018) - 2017
- [j30]Yuri Murillo, Bertold Van den Bergh, Jona Beysens, Alexander Bertrand, Wim Dehaene, Panagiotis Patrinos, Tinne Tuytelaars, Ruth Vazquez Sabariego, Marian Verhelst, Patrick Wambacq, Sofie Pollin:
Multidisciplinary Learning through Implementation of the DVB-S2 Standard. IEEE Commun. Mag. 55(5): 124-130 (2017) - [j29]Bert Moons, Marian Verhelst:
An Energy-Efficient Precision-Scalable ConvNet Processor in 40-nm CMOS. IEEE J. Solid State Circuits 52(4): 903-914 (2017) - [j28]Venkata Rajesh Pamula, Jose Manuel Valero-Sarmiento, Long Yan, Alper Bozkurt, Chris Van Hoof, Nick Van Helleputte, Refet Firat Yazicioglu, Marian Verhelst:
A 172 µW Compressively Sampled Photoplethysmographic (PPG) Readout ASIC With Heart Rate Estimation Directly From Compressively Sampled Data. IEEE Trans. Biomed. Circuits Syst. 11(3): 487-496 (2017) - [j27]Juan Carlos Pena Ramos, Marian Verhelst:
Split-Delta Background Calibration for SAR ADCs. IEEE Trans. Circuits Syst. II Express Briefs 64-II(2): 221-225 (2017) - [j26]Fernando de la Hucha Arce, Marc Moonen, Marian Verhelst, Alexander Bertrand:
Adaptive Quantization for Multichannel Wiener Filter-Based Speech Enhancement in Wireless Acoustic Sensor Networks. Wirel. Commun. Mob. Comput. 2017 (2017) - [c62]Leonardo Cecconi, Sander Smets, Luca Benini, Marian Verhelst:
Optimal Tiling Strategy for Memory Bandwidth Reduction for CNNs. ACIVS 2017: 89-100 - [c61]Fernando Rosas, Konstantinos Manolakis, Christian Oberli, Mohammad Mahdi Azari, Marian Verhelst, Sofie Pollin:
Impact of interference correlation on the decoding error statistics. ACSSC 2017: 1115-1119 - [c60]Bert Moons, Koen Goetschalckx, Nick Van Berckelaer, Marian Verhelst:
Minimum energy quantized neural networks. ACSSC 2017: 1921-1925 - [c59]Martin Andraud, Gönenç Berkol, Jaro De Roose, Santosh Gannavarapu, Haoming Xin, Eugenio Cantatore, Pieter J. A. Harpe, Marian Verhelst, Peter G. M. Baltus:
Exploring the unknown through successive generations of low power and low resource versatile agents. DATE 2017: 290-293 - [c58]Bert Moons, Roel Uytterhoeven, Wim Dehaene, Marian Verhelst:
DVAFS: Trading computational accuracy for energy through dynamic-voltage-accuracy-frequency-scaling. DATE 2017: 488-493 - [c57]Gert Dekkers, Steven Lauwereins, Bart Thoen, Mulu Weldegebreal Adhana, Henk Brouckxon, Bertold Van den Bergh, Toon van Waterschoot, Bart Vanrumste, Marian Verhelst, Peter Karsmakers:
The SINS Database for Detection of Daily Activities in a Home Environment Using an Acoustic Sensor Network. DCASE 2017: 32-36 - [c56]Ahmed Hallawa, Jaro De Roose, Martin Andraud, Marian Verhelst, Gerd Ascheid:
Instinct-driven dynamic hardware reconfiguration: evolutionary algorithm optimized compression for autonomous sensory agents. GECCO (Companion) 2017: 1727-1734 - [c55]Tom R. Molderez, Bas de Wit, Korneel Rabaey, Marian Verhelst:
Successive parabolic interpolation as extremum seeking control for microbial fuel & electrolysis cells. IECON 2017: 3128-3133 - [c54]Bert Moons, Roel Uytterhoeven, Wim Dehaene, Marian Verhelst:
14.5 Envision: A 0.26-to-10TOPS/W subword-parallel dynamic-voltage-accuracy-frequency-scalable Convolutional Neural Network processor in 28nm FDSOI. ISSCC 2017: 246-247 - [c53]Meng-Fan Chang, Jun Deguchi, Vivek De, Masato Motomura, Shinichiro Shiratake, Marian Verhelst:
F3: Beyond the horizon of conventional computing: From deep learning to neuromorphic systems. ISSCC 2017: 506-508 - [c52]Thomas Bos, Komail M. H. Badami, Wim Dehaene, Marian Verhelst:
An 8-11b 320kS/s resolution scalable noise shaping SAR ADC. NEWCAS 2017: 209-212 - [i4]Bert Moons, Koen Goetschalckx, Nick Van Berckelaer, Marian Verhelst:
Minimum Energy Quantized Neural Networks. CoRR abs/1711.00215 (2017) - 2016
- [j25]Fernando Rosas, Vasilis Ntranos, Christopher J. Ellison, Sofie Pollin, Marian Verhelst:
Understanding Interdependency Through Complex Information Sharing. Entropy 18(2): 38 (2016) - [j24]Komail M. H. Badami, Steven Lauwereins, Wannes Meert, Marian Verhelst:
A 90 nm CMOS, 6µW Power-Proportional Acoustic Sensing Frontend for Voice Activity Detection. IEEE J. Solid State Circuits 51(1): 291-302 (2016) - [j23]Fernando de la Hucha Arce, Fernando Rosas, Marc Moonen, Marian Verhelst, Alexander Bertrand:
Generalized Signal Utility for LMMSE Signal Estimation With Application to Greedy Quantization in Wireless Sensor Networks. IEEE Signal Process. Lett. 23(9): 1202-1206 (2016) - [j22]Antti Anttonen, Adrian Kotelba, Marian Verhelst, Aarne Mämmelä:
Finite-Horizon Prediction of Energy Depletions in Off-Grid Wireless Networks. IEEE Trans. Veh. Technol. 65(8): 6731-6736 (2016) - [j21]Fernando Rosas, Richard Demo Souza, Marcelo Eduardo Pellenz, Christian Oberli, Glauber Gomes de Oliveira Brante, Marian Verhelst, Sofie Pollin:
Optimizing the Code Rate of Energy-Constrained Wireless Communications With HARQ. IEEE Trans. Wirel. Commun. 15(1): 191-205 (2016) - [c51]Laura Isabel Galindez Olascoaga, Komail M. H. Badami, V. Rajesh Pamula, Steven Lauwereins, Wannes Meert, Marian Verhelst:
Exploiting system configurability towards dynamic accuracy-power trade-offs in sensor front-ends. ACSSC 2016: 1027-1031 - [c50]V. Rajesh Pamula, Marian Verhelst, Chris Van Hoof, Refet Firat Yazicioglu:
A 17nA, 47.2dB dynamic range, adaptive sampling controller for online data rate reduction in low power ECG systems. BioCAS 2016: 272-275 - [c49]Tom Vermeulen, Fernando Rosas, Marian Verhelst, Sofie Pollin:
Performance analysis of in-band full duplex collision and interference detection in dense networks. CCNC 2016: 595-601 - [c48]Daniele Bortolotti, Andrea Bartolini, Luca Benini, V. Rajesh Pamula, Nick Van Helleputte, Chris Van Hoof, Marian Verhelst, Tobias Gemmeke, Rubén Braojos Lopez, Giovanni Ansaloni, David Atienza, Pierre Vandergheynst:
PHIDIAS: ultra-low-power holistic design for smart bio-signals computing platforms. Conf. Computing Frontiers 2016: 309-314 - [c47]Sander Smets, Toon Goedemé, Marian Verhelst:
Custom processor design for efficient, yet flexible Lucas-Kanade optical flow. DASIP 2016: 138-145 - [c46]Laura Isabel Galindez Olascoaga, Wannes Meert, Herman Bruyninckx, Marian Verhelst:
Extending Naive Bayes with Precision-tunable Feature Variables for Resource-efficient Sensor Fusion. AI-IoT@ECAI 2016: 23-30 - [c45]Komail M. H. Badami, V. Rajesh Pamula, Marian Verhelst:
A switched-capacitor degenerated, scalable gm-C filter-bank for acoustic front-ends. ISCAS 2016: 818-821 - [c44]Paul Liang, Marian Verhelst:
Session 14 overview: Next-generation processing. ISSCC 2016: 252-253 - [c43]Pamula Venkata Rajesh, Jose Manuel Valero-Sarmiento, Long Yan, Alper Bozkurt, Chris Van Hoof, Nick Van Helleputte, Refet Firat Yazicioglu, Marian Verhelst:
22.4 A 172µW compressive sampling photoplethysmographic readout with embedded direct heart-rate and variability extraction from compressively sampled data. ISSCC 2016: 386-387 - [c42]Vivek De, Kerry Bernstein, Takefumi Yoshikawa, Yusuf Leblebici, Marian Verhelst, Mahesh Mehendale, Makoto Nagata:
F1: Designing secure systems: Manufacturing, circuits and architectures. ISSCC 2016: 492-494 - [c41]Bert Moons, Marian Verhelst:
A 0.3-2.6 TOPS/W precision-scalable processor for real-time large-scale ConvNets. VLSI Circuits 2016: 1-2 - [c40]Bert Moons, Bert De Brabandere, Luc Van Gool, Marian Verhelst:
Energy-efficient ConvNets through approximate computing. WACV 2016: 1-8 - [i3]Bert Moons, Bert De Brabandere, Luc Van Gool, Marian Verhelst:
Energy-Efficient ConvNets Through Approximate Computing. CoRR abs/1603.06777 (2016) - [i2]Bert Moons, Marian Verhelst:
A 0.3-2.6 TOPS/W Precision-Scalable Processor for Real-Time Large-Scale ConvNets. CoRR abs/1606.05094 (2016) - 2015
- [j20]Steven Lauwereins, Komail M. H. Badami, Wannes Meert, Marian Verhelst:
Optimal resource usage in ultra-low-power sensor interfaces through context- and resource-cost-aware machine learning. Neurocomputing 169: 236-245 (2015) - [j19]Angelo Nagari, Kenichi Okada, Marian Verhelst:
Introduction to the Special Issue on the 40th European Solid-State Circuits Conference (ESSCIRC). IEEE J. Solid State Circuits 50(7): 1512-1515 (2015) - [j18]Paramartha Indirayanti, Tuba Ayhan, Marian Verhelst, Wim Dehaene, Patrick Reynaert:
A mm-Precise 60 GHz Transmitter in 40 nm CMOS for Discrete-Carrier Indoor Localization. IEEE J. Solid State Circuits 50(7): 1604-1617 (2015) - [j17]Chunshu Li, Min Li, Marian Verhelst, André Bourdoux, Liesbet Van der Perre, Sofie Pollin:
On the General Mathematical Framework, Calibration/Compensation Method, and Applications of Non-Ideal Software Defined Harmonics Rejection Transceivers. IEEE Trans. Circuits Syst. I Regul. Pap. 62-I(1): 292-301 (2015) - [j16]Chunshu Li, Min Li, Marian Verhelst, André Bourdoux, Mark Ingels, Liesbet Van der Perre, Sofie Pollin:
Efficient Timing Mismatch Correction for Low-Cost Digital-Mixing Transmitter. IEEE Trans. Signal Process. 63(24): 6553-6564 (2015) - [j15]Afsaneh Nassery, Srinath Byregowda, Sule Ozev, Marian Verhelst, Mustapha Slamani:
Built-In Self-Test of Transmitter I/Q Mismatch and Nonlinearity Using Self-Mixing Envelope Detector. IEEE Trans. Very Large Scale Integr. Syst. 23(2): 331-341 (2015) - [j14]Chunshu Li, Min Li, Khaled Khalaf, André Bourdoux, Marian Verhelst, Mark Ingels, Piet Wambacq, Jan Craninckx, Liesbet Van der Perre, Sofie Pollin:
Opportunities and Challenges of Digital Signal Processing in Deeply Technology-Scaled Transceivers. J. Signal Process. Syst. 78(1): 5-19 (2015) - [c39]Fernando Rosas, Mohammad Mahdi Azari, Bertold Van den Bergh, Richard Demo Souza, Sofie Pollin, Marian Verhelst:
Using mobility for increasing the energy efficiency of multihop communications. ACSSC 2015: 469-474 - [c38]Tom Vermeulen, Fernando Rosas, Barend van Liempd, Marian Verhelst, Sofie Pollin:
An energy-scalable in-band full duplex architecture. CAMAD 2015: 22-26 - [c37]Fernando de la Hucha Arce, Fernando Rosas, Marc Moonen, Marian Verhelst, Alexander Bertrand:
Energy-vs-performance trade-offs in speech enhancement in wireless acoustic sensor networks. EUSIPCO 2015: 1561-1565 - [c36]Chunshu Li, André Bourdoux, Marian Verhelst, Yanxiang Huang, Min Li, Liesbet Van der Perre, Sofie Pollin:
<30 mW rectangular-to-polar conversion processor in 802.11ad polar transmitter. ICASSP 2015: 1022-1026 - [c35]Juan Carlos Pena Ramos, Marian Verhelst:
Redundancy effect on the performance of digitally-assisted SAR ADCs. ICECS 2015: 276-279 - [c34]Bert Moons, Marian Verhelst:
DVAS: Dynamic Voltage Accuracy Scaling for increased energy-efficiency in approximate computing. ISLPED 2015: 237-242 - [c33]Komail M. H. Badami, Steven Lauwereins, Wannes Meert, Marian Verhelst:
24.2 Context-aware hierarchical information-sensing in a 6μW 90nm CMOS voice activity detector. ISSCC 2015: 1-3 - [c32]Marian Verhelst, Dennis Sylvester, Makoto Takamiya, Mike Clinton, Kathy Wilcox, Koichi Nose:
F4: Building the Internet of Everything (IoE): Low-power techniques at the circuit and system levels. ISSCC 2015: 1-2 - [c31]Fernando Rosas, Richard Demo Souza, Marian Verhelst, Sofie Pollin:
Energy-efficient MIMO multihop communications using the antenna selection scheme. ISWCS 2015: 686-690 - [i1]Fernando Rosas, Vasilis Ntranos, Christopher J. Ellison, Sofie Pollin, Marian Verhelst:
Understanding interdependency through complex information sharing. CoRR abs/1509.04555 (2015) - 2014
- [j13]Bertold Van den Bergh, Tom Vermeulen, Marian Verhelst, Sofie Pollin:
CLAWS: Cross-Layer Adaptable Wireless System enabling full cross-layer experimentation on real-time software-defined 802.15.4. EURASIP J. Wirel. Commun. Netw. 2014: 187 (2014) - [j12]Bert Moons, Marian Verhelst:
Energy-Efficiency and Accuracy of Stochastic Computing Circuits in Emerging Technologies. IEEE J. Emerg. Sel. Topics Circuits Syst. 4(4): 475-486 (2014) - [c30]V. Rajesh Pamula, Marian Verhelst, Chris Van Hoof, Refet Firat Yazicioglu:
Computationally-efficient compressive sampling for low-power pulseoximeter system. BioCAS 2014: 69-72 - [c29]Steven Lauwereins, Komail M. H. Badami, Wannes Meert, Marian Verhelst:
Context- and cost-aware feature selection in ultra-low-power sensor interfaces. ESANN 2014 - [c28]Paramartha Indirayanti, Tuba Ayhan, Marian Verhelst, Wim Dehaene, Patrick Reynaert:
A 60GHz transmitter in 40nm CMOS achieving mm-precision for discrete-carrier localization. ESSCIRC 2014: 291-294 - [c27]Tuba Ayhan, Wim Dehaene, Marian Verhelst:
A 128∶2048/1536 point FFT hardware implementation with output pruning. EUSIPCO 2014: 266-270 - [c26]Iman Khajenasiri, Edoardo Patti, Marco Jahn, Andrea Acquaviva, Marian Verhelst, Enrico Macii, Georges G. E. Gielen:
Design and implementation of a multi-standard event-driven energy management system for smart buildings. GCCE 2014: 20-21 - [c25]Chunshu Li, Min Li, Mark Ingels, Marian Verhelst, Xiaoqiang Zhang, Joris Van Driessche, André Bourdoux, Liesbet Van der Perre, Sofie Pollin:
Efficient duty-cycle mismatch compensation in digital transmitter. ICASSP 2014: 4998-5002 - [c24]Tom Redant, Tuba Ayhan, Nico De Clercq, Marian Verhelst, Patrick Reynaert, Wim Dehaene:
20.1 A 40nm CMOS receiver for 60GHz discrete-carrier indoor localization achieving mm-precision at 4m range. ISSCC 2014: 342-343 - [c23]Steven Lauwereins, Wannes Meert, Jort F. Gemmeke, Marian Verhelst:
Ultra-low-power voice-activity-detector through context- and resource-cost-aware feature selection in decision trees. MLSP 2014: 1-6 - [c22]Bert Moons, Marian Verhelst:
Energy and accuracy in multi-stage stochastic computing. NEWCAS 2014: 197-200 - [c21]Tuba Ayhan, Marian Verhelst, Wim Dehaene:
Impact of multipath fading on a precise 60 GHz indoor locationing system. SIU 2014: 1841-1844 - 2013
- [j11]Hasnain Lakdawala, Mark Schaecher, Chang-Tsung Fu, Rahul Dilip Limaye, Jon Duster, Yulin Tan, Ajay Balankutty, Erkan Alpman, Chun C. Lee, Khoa Minh Nguyen, Hyung-Jin Lee, Ashoke Ravi, Satoshi Suzuki, Brent R. Carlton, Hyung Seok Kim, Marian Verhelst, Stefano Pellerano, Tong Kim, Satish Venkatesan, Durgesh Srivastava, Peter Vandervoorn, Jad Rizk, Chia-Hong Jan, Sunder Ramamurthy, Raj Yavatkar, Krishnamurthy Soumyanath:
A 32 nm SoC With Dual Core ATOM Processor and RF WiFi Transceiver. IEEE J. Solid State Circuits 48(1): 91-103 (2013) - [j10]Jorge Carballido, Jorge Hermosillo, Arturo Veloz-Guerrero, David Arditti, Alberto Del Rio, Edgar Borrayo Sandoval, Manuel E. Guzman-Renteria, Hasnain Lakdawala, Marian Verhelst:
A Programmable Calibration/BIST Engine for RF and Analog Blocks in SoCs Integrated in a 32 nm CMOS WiFi Transceiver. IEEE J. Solid State Circuits 48(7): 1669-1679 (2013) - [c20]Chunshu Li, Min Li, Marian Verhelst, Sofie Pollin, André Bourdoux, Liesbet Van der Perre:
Adaptive filter based low complexity digital intensive harmonic rejection for SDR receiver. ICASSP 2013: 2712-2715 - [c19]Juan Carlos Pena Ramos, Marian Verhelst:
Flexible, ultra-low power sensor nodes through configurable finite state machines. ReCoSoC 2013: 1-7 - [c18]Chunshu Li, Min Li, Mark Ingels, Xiaoqiang Zhang, Marian Verhelst, Sofie Pollin, Joris Van Driessche, André Bourdoux, Liesbet Van der Perre:
Efficient self-correction scheme for static non-idealities in nano-scale quadrature digital RF transmitters. SiPS 2013: 71-76 - [c17]Tuba Ayhan, Wim Dehaene, Marian Verhelst:
A method for using sub-Nyquist sampling for ultra low-power positioning systems. SiPS 2013: 100-105 - 2012
- [j9]Ashoke Ravi, Paolo Madoglio, Hongtao Xu, Kailash Chandrashekar, Marian Verhelst, Stefano Pellerano, Luis Cuellar, Mariano Aguirre-Hernandez, Masoud Sajadieh, J. E. Zarate-Roldan, Ofir Bochobza-Degani, Hasnain Lakdawala, Yorgos Palaskas:
A 2.4-GHz 20-40-MHz Channel WLAN Digital Outphasing Transmitter Utilizing a Delay-Based Wideband Phase Modulator in 32-nm CMOS. IEEE J. Solid State Circuits 47(12): 3184-3196 (2012) - [j8]Afsaneh Nassery, Osman Emir Erol, Sule Ozev, Marian Verhelst:
Test Signal Development and Analysis for OFDM Systems RF Front-End Parameter Extraction. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 31(6): 958-967 (2012) - [j7]Shreyas Sen, Debashis Banerjee, Marian Verhelst, Abhijit Chatterjee:
A Power-Scalable Channel-Adaptive Wireless Receiver Based on Built-In Orthogonally Tunable LNA. IEEE Trans. Circuits Syst. I Regul. Pap. 59-I(5): 946-957 (2012) - [c16]Jorge Hermosillo, Jorge Carballido, Arturo Veloz-Guerrero, David Arditti, Alberto Del Rio, Edgar Borrayo Sandoval, Manuel E. Guzman-Renteria, Hasnain Lakdawala, Marian Verhelst:
A programmable calibration/BIST engine for RF/analog blocks in SoCs. ESSCIRC 2012: 133-136 - [c15]Hasnain Lakdawala, Mark Schaecher, Chang-Tsung Fu, Rahul Dilip Limaye, Jon Duster, Yulin Tan, Ajay Balankutty, Erkan Alpman, Chun C. Lee, Satoshi Suzuki, Brent R. Carlton, Hyung Seok Kim, Marian Verhelst, Stefano Pellerano, Tong Kim, Durgesh Srivastava, Satish Venkatesan, Hyung-Jin Lee, Peter Vandervoorn, Jad Rizk, Chia-Hong Jan, Krishnamurthy Soumyanath, Sunder Ramamurthy:
32nm x86 OS-compliant PC on-chip with dual-core Atom® processor and RF WiFi transceiver. ISSCC 2012: 62-64 - [c14]Paolo Madoglio, Ashoke Ravi, Hongtao Xu, Kailash Chandrashekar, Marian Verhelst, Stefano Pellerano, Luis Cuellar, Mariano Aguirre, Masoud Sajadieh, Ofir B. Degani, Hasnain Lakdawala, Yorgos Palaskas:
A 20dBm 2.4GHz digital outphasing transmitter for WLAN application in 32nm CMOS. ISSCC 2012: 168-170 - [c13]Chunshu Li, Min Li, Sofie Pollin, Björn Debaillie, Marian Verhelst, Liesbet Van der Perre, Rudy Lauwereins:
Reduced Complexity On-chip IQ-Imbalance Self-Calibration. SiPS 2012: 31-36 - [c12]Chunshu Li, Min Li, Marian Verhelst, André Bourdoux, Jonathan Borremans, Sofie Pollin, Alessandro Chiumento, Liesbet Van der Perre, Rudy Lauwereins:
A Generic Framework for Optimizing Digital Intensive Harmonic Rejection Receivers. SiPS 2012: 167-172 - [c11]Tuba Ayhan, Tom Redant, Marian Verhelst, Wim Dehaene:
Towards a Fast and Hardware Efficient Sub-MM Precision Ranging System. SiPS 2012: 203-208 - [c10]Afsaneh Nassery, Srinath Byregowda, Sule Ozev, Marian Verhelst, Mustapha Slamani:
Built-in-Self Test of transmitter I/Q mismatch using self-mixing envelope detector. VTS 2012: 56-61 - 2011
- [j6]An He, Srikathyayani Srikanteswara, Kyung Kyoon Bae, Timothy R. Newman, Jeffrey H. Reed, William H. Tranter, Masoud Sajadieh, Marian Verhelst:
Power Consumption Minimization for MIMO Systems - A Cognitive Radio Approach. IEEE J. Sel. Areas Commun. 29(2): 469-479 (2011) - [j5]Sidharth Balasubramanian, Gregory L. Creech, J. Wilson, Samantha M. Yoder, Jamin J. McCue, Marian Verhelst, Waleed Khalil:
Systematic Analysis of Interleaved Digital-to-Analog Converters. IEEE Trans. Circuits Syst. II Express Briefs 58-II(12): 882-886 (2011) - [c9]Afsaneh Nassery, Sule Ozev, Marian Verhelst, Mustapha Slamani:
Extraction of EVM from Transmitter System Parameters. ETS 2011: 75-80 - [c8]Shreyas Sen, Marian Verhelst, Abhijit Chatterjee:
Orthogonally tunable inductorless RF LNA for adaptive wireless systems. ISCAS 2011: 285-288 - 2010
- [j4]Nick Van Helleputte, Marian Verhelst, Wim Dehaene, Georges G. E. Gielen:
A Reconfigurable, 130 nm CMOS 108 pJ/pulse, Fully Integrated IR-UWB Receiver for Communication and Precise Ranging. IEEE J. Solid State Circuits 45(1): 69-83 (2010)
2000 – 2009
- 2009
- [c7]Wim Dehaene, Georges G. E. Gielen, Michiel Steyaert, Hans Danneels, V. Desmedt, Christophe De Roover, Z. Li, Marian Verhelst, Nick Van Helleputte, S. Radioma, C. Walravensa, L. Pleysier:
RFID, where are they? ESSCIRC 2009: 36-43 - [c6]Marian Verhelst, Nick Van Helleputte, Georges G. E. Gielen, Wim Dehaene:
A reconfigurable, 0.13µm CMOS 110pJ/pulse, fully integrated IR-UWB receiver for communication and sub-cm ranging. ISSCC 2009: 250-251 - 2008
- [j3]Marian Verhelst, Wim Dehaene:
A Flexible, Ultra-Low-Energy 35 pJ/Pulse Digital Back-End for a QAC IR-UWB Receiver. IEEE J. Solid State Circuits 43(7): 1677-1687 (2008) - [j2]Marian Verhelst, Wim Dehaene:
Analysis of the QAC IR-UWB Receiver for Low Energy, Low Data-Rate Communication. IEEE Trans. Circuits Syst. I Regul. Pap. 55-I(8): 2423-2432 (2008) - [c5]Marian Verhelst, Julien Ryckaert, Yves Vanderperren, Wim Dehaene:
A Low Power, Reconfigurable IR-UWB System. ICC 2008: 3770-3774 - [c4]Hans Danneels, Marian Verhelst, Pieter Palmers, Wim Vereecken, Bruno Boury, Wim Dehaene, Michiel Steyaert, Georges G. E. Gielen:
A low-power mixing DAC IR-UWB-receiver. ISCAS 2008: 2697-2700 - 2007
- [j1]Julien Ryckaert, Marian Verhelst, Mustafa Badaroglu, Stefano D'Amico, Vincent De Heyn, Claude Desset, Pierluigi Nuzzo, Bart van Poucke, Piet Wambacq, Andrea Baschirotto, Wim Dehaene, Geert Van der Plas:
A CMOS Ultra-Wideband Receiver for Low Data-Rate Communication. IEEE J. Solid State Circuits 42(11): 2515-2527 (2007) - [c3]Marian Verhelst, Wim Dehaene:
A flexible, ultra-low power 35pJ/pulse digital back-end for a QAC UWB receiver. ESSCIRC 2007: 236-239 - 2005
- [c2]Marian Verhelst, Wim Dehaene:
System design of an ultra-low power, low data rate, pulsed UWB receiver in the 0-960 MHz band. ICC 2005: 2812-2817 - 2004
- [c1]Marian Verhelst, Wim Vereecken, Michiel Steyaert, Wim Dehaene:
Architectures for low power ultra-wideband radio receivers in the 3.1-5GHz band for data rates < 10Mbps. ISLPED 2004: 280-285
Coauthor Index
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