| Minimum energy quantized neural networks B Moons, K Goetschalckx, N Van Berckelaer, M Verhelst 2017 51st Asilomar Conference on Signals, Systems, and Computers, 1921-1925, 2018 | 180 | 2018 |
| Breaking High-Resolution CNN Bandwidth Barriers With Enhanced Depth-First Execution K Goetschalckx, M Verhelst IEEE Journal on Emerging and Selected Topics in Circuits and Systems 9 (2 …, 2019 | 62 | 2019 |
| DepFiN: A 12nm, 3.8 TOPs depth-first CNN processor for high res. image processing K Goetschalckx, M Verhelst 2021 Symposium on VLSI Circuits, 1-2, 2021 | 40 | 2021 |
| Optimized hierarchical cascaded processing K Goetschalckx, B Moons, S Lauwereins, M Andraud, M Verhelst IEEE Journal on Emerging and Selected Topics in Circuits and Systems 8 (4 …, 2018 | 32 | 2018 |
| DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling L Mei, K Goetschalckx, A Symons, M Verhelst 2023 IEEE International Symposium on High-Performance Computer Architecture …, 2023 | 28 | 2023 |
| Efficiently combining svd, pruning, clustering and retraining for enhanced neural network compression K Goetschalckx, B Moons, P Wambacq, M Verhelst Proceedings of the 2nd International Workshop on Embedded and Mobile Deep …, 2018 | 21 | 2018 |
| DepFiN: A 12-nm Depth-First, High-Resolution CNN Processor for IO-Efficient Inference K Goetschalckx, F Wu, M Verhelst IEEE Journal of Solid-State Circuits 58 (5), 1425-1435, 2022 | 11 | 2022 |
| 11.3 Metis AIPU: A 12nm 15TOPS/W 209.6 TOPS SoC for Cost-and Energy-Efficient Inference at the Edge PA Hager, B Moons, S Cosemans, IA Papistas, B Rooseleer, J Van Loon, ... 2024 IEEE International Solid-State Circuits Conference (ISSCC) 67, 212-214, 2024 | | 2024 |
| Optimizing Embedded Vision Efficiency across the Hardware-dataflow-algorithm Stack K Goetschalckx | | 2023 |
