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Koen Goetschalckx
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Journal Articles
- 2023
- [j3]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) - 2019
- [j2]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) - 2018
- [j1]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)
Conference and Workshop Papers
- 2024
- [c5]Pascal Alexander Hager, Bert Moons, Stefan Cosemans, Ioannis A. Papistas, Bram Rooseleer, Jeroen Van Loon, Roel Uytterhoeven, Florian Zaruba, Spyridoula Koumousi, Milos Stanisavljevic, Stefan Mach, Sebastiaan Mutsaards, Riduan Khaddam Aljameh, Gua Hao Khov, Brecht Machiels, Cristian Olar, Anastasios Psarras, Sander Geursen, Jeroen Vermeeren, Yi Lu, Abhishek Maringanti, Deepak Ameta, Leonidas Katselas, Noah Hütter, Manuel Schmuck, Swetha Sivadas, Karishma Sharma, Manuel Oliveira, Ramon Aerne, Nitish Sharma, Timir Soni, Beatrice Bussolino, Djordje Pesut, Michele Pallaro, Andrei Podlesnii, Alexios Lyrakis, Yannick Ruffiner, Martino Dazzi, Johannes Thiele, Koen Goetschalckx, Nazareno Bruschi, Jonas Doevenspeck, Bram Verhoef, Stefan Linz, Giuseppe Garcea, Jonathan Ferguson, Ioannis Koltsidas, Evangelos Eleftheriou:
11.3 Metis AIPU: A 12nm 15TOPS/W 209.6TOPS SoC for Cost- and Energy-Efficient Inference at the Edge. ISSCC 2024: 212-214 - 2023
- [c4]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 - 2021
- [c3]Koen Goetschalckx, Marian Verhelst:
DepFiN: A 12nm, 3.8TOPs depth-first CNN processor for high res. image processing. VLSI Circuits 2021: 1-2 - 2018
- [c2]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 - 2017
- [c1]Bert Moons, Koen Goetschalckx, Nick Van Berckelaer, Marian Verhelst:
Minimum energy quantized neural networks. ACSSC 2017: 1921-1925
Data and Artifacts
- 2022
- [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
Informal and Other Publications
- 2022
- [i2]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) - 2017
- [i1]Bert Moons, Koen Goetschalckx, Nick Van Berckelaer, Marian Verhelst:
Minimum Energy Quantized Neural Networks. CoRR abs/1711.00215 (2017)
Coauthor Index
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