Arne Symons

23 papers A* 2A 2B 2Journal 12Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
An Analytical Model for Performance-Carbon Co-Optimization of Edge AI Accelerators.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Jiacong Sun, Xiaoling Yi, Arne Symons, Georges G. E. Gielen, Lieven Eeckhout, Marian Verhelst
2026 J jnl
MONET: Modeling and Optimization of neural NEtwork Training from Edge to Data Centers.
CoRR
Jérémy Morlier, Robin Geens, Stef Cuyckens, Arne Symons, Marian Verhelst, Vincent Gripon, Mathieu Léonardon
2025 A conf
A 3D Design Methodology for Integrated Wearable SoCs: Enabling Energy Efficiency and Enhanced Performance at Iso-Area Footprint.
DATE
Huseyin Ekin Sumbul, Arne Symons, Lita Yang, Huichu Liu, Tony F. Wu, Matheus Trevisan Moreira, Debabrata Mohapatra, Abhinav Agarwal, Kaushik Ravindran, Chris Thompson, Yuecheng Li, Edith Beigné
2025 A* conf
Anda: Unlocking Efficient LLM Inference with a Variable-Length Grouped Activation Data Format.
HPCA
Chao Fang, Man Shi, Robin Geens, Arne Symons, Zhongfeng Wang, Marian Verhelst
2025 B conf
Fine-Grained Fusion: The Missing Piece in Area-Efficient State Space Model Acceleration.
PACT
Robin Geens, Arne Symons, Marian Verhelst
2025 J jnl
Fine-Grained Fusion: The Missing Piece in Area-Efficient State Space Model Acceleration.
CoRR
Robin Geens, Arne Symons, Marian Verhelst
2025 J jnl
Hardware-aware Neural Architecture Search of Early Exiting Networks on Edge Accelerators.
CoRR
Alaa Zniber, Arne Symons, Ouassim Karrakchou, Marian Verhelst, Mounir Ghogho
2025 J jnl
MATCH: Model-Aware TVM-Based Compilation for Heterogeneous Edge Devices.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Mohamed Amine Hamdi, Francesco Daghero, Giuseppe Maria Sarda, Josse Van Delm, Arne Symons, Luca Benini, Marian Verhelst, Daniele Jahier Pagliari, Alessio Burrello
2025 J jnl
Stream: Design Space Exploration of Layer-Fused DNNs on Heterogeneous Dataflow Accelerators.
IEEE Trans. Computers
Arne Symons, Linyan Mei, Steven Colleman, Pouya Houshmand, Sebastian Karl, Marian Verhelst
2024 J jnl
Anda: Unlocking Efficient LLM Inference with a Variable-Length Grouped Activation Data Format.
CoRR
Chao Fang, Man Shi, Robin Geens, Arne Symons, Zhongfeng Wang, Marian Verhelst
2024 — conf
Energy Cost Modelling for Optimizing Large Language Model Inference on Hardware Accelerators.
SOCC
Robin Geens, Man Shi, Arne Symons, Chao Fang, Marian Verhelst
2024 J jnl
MATCH: Model-Aware TVM-based Compilation for Heterogeneous Edge Devices.
CoRR
Mohamed Amine Hamdi, Francesco Daghero, Giuseppe Maria Sarda, Josse Van Delm, Arne Symons, Luca Benini, Marian Verhelst, Daniele Jahier Pagliari, Alessio Burrello
2024 — conf
Optimizing Layer-Fused Scheduling of Transformer Networks on Multi-accelerator Platforms.
ISQED
Steven Colleman, Arne Symons, Victor J. B. Jung, Marian Verhelst
2024 J jnl
Optimizing Layer-Fused Scheduling of Transformer Networks on Multi-accelerator Platforms.
CoRR
Steven Colleman, Arne Symons, Victor J. B. Jung, Marian Verhelst
2023 A* conf
DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling.
HPCA
Linyan Mei, Koen Goetschalckx, Arne Symons, Marian Verhelst
2023 A conf
Genetic Algorithm-based Framework for Layer-Fused Scheduling of Multiple DNNs on Multi-core Systems.
DATE
Sebastian Karl, Arne Symons, Nael Fasfous, Marian Verhelst
2023 — conf
Hardware-aware NAS by Genetic Optimisation with a Design Space Exploration Simulator.
CVPR Workshops
Lotte Hendrickx, Arne Symons, Wiebe Van Ranst, Marian Verhelst, Toon Goedemé
2023 — conf
SALSA: Simulated Annealing based Loop-Ordering Scheduler for DNN Accelerators.
AICAS
Victor J. B. Jung, Arne Symons, Linyan Mei, Marian Verhelst, Luca Benini
2023 J jnl
SALSA: Simulated Annealing based Loop-Ordering Scheduler for DNN Accelerators.
CoRR
Victor J. B. Jung, Arne Symons, Linyan Mei, Marian Verhelst, Luca Benini
2023 B conf
Stream: A Modeling Framework for Fine-grained Layer Fusion on Multi-core DNN Accelerators.
ISPASS
Arne Symons, Linyan Mei, Steven Colleman, Pouya Houshmand, Sebastian Karl, Marian Verhelst
2022 J jnl
DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling.
CoRR
Linyan Mei, Koen Goetschalckx, Arne Symons, Marian Verhelst
2022 J jnl
Towards Heterogeneous Multi-core Accelerators Exploiting Fine-grained Scheduling of Layer-Fused Deep Neural Networks.
CoRR
Arne Symons, Linyan Mei, Steven Colleman, Pouya Houshmand, Sebastian Karl, Marian Verhelst
2021 — conf
LOMA: Fast Auto-Scheduling on DNN Accelerators through Loop-Order-based Memory Allocation.
AICAS
Arne Symons, Linyan Mei, Marian Verhelst