Arne Symons

According to our database, Arne Symons authored at least 18 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

An Analytical Model for Performance-Carbon Co-Optimization of Edge AI Accelerators.

Jiacong Sun, Xiaoling Yi, Arne Symons, Georges G. E. Gielen, Lieven Eeckhout, Marian Verhelst

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., March, 2026

MONET: Modeling and Optimization of neural NEtwork Training from Edge to Data Centers.

Jérémy Morlier, Robin Geens, Stef Cuyckens, Arne Symons, Marian Verhelst, Vincent Gripon, Mathieu Léonardon

CoRR, March, 2026

2025

Hardware-aware Neural Architecture Search of Early Exiting Networks on Edge Accelerators.

Alaa Zniber, Arne Symons, Ouassim Karrakchou, Marian Verhelst, Mounir Ghogho

CoRR, December, 2025

MATCH: Model-Aware TVM-Based Compilation for Heterogeneous Edge Devices.

Mohamed Amine Hamdi, Francesco Daghero, Giuseppe Maria Sarda, Josse Van Delm, Arne Symons, Luca Benini, Marian Verhelst, Daniele Jahier Pagliari, Alessio Burrello

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., October, 2025

Stream: Design Space Exploration of Layer-Fused DNNs on Heterogeneous Dataflow Accelerators.

Arne Symons, Linyan Mei, Steven Colleman, Pouya Houshmand, Sebastian Karl, Marian Verhelst

IEEE Trans. Computers, January, 2025

Anda: Unlocking Efficient LLM Inference with a Variable-Length Grouped Activation Data Format.

Chao Fang, Man Shi, Robin Geens, Arne Symons, Zhongfeng Wang, Marian Verhelst

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2025

A 3D Design Methodology for Integrated Wearable SoCs: Enabling Energy Efficiency and Enhanced Performance at Iso-Area Footprint.

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

Proceedings of the Design, Automation & Test in Europe Conference, 2025

Fine-Grained Fusion: The Missing Piece in Area-Efficient State Space Model Acceleration.

Robin Geens, Arne Symons, Marian Verhelst

Proceedings of the 34th International Conference on Parallel Architectures and Compilation Techniques, 2025

2024

Energy Cost Modelling for Optimizing Large Language Model Inference on Hardware Accelerators.

Robin Geens, Man Shi, Arne Symons, Chao Fang, Marian Verhelst

Proceedings of the 37th IEEE International System-on-Chip Conference, 2024

Optimizing Layer-Fused Scheduling of Transformer Networks on Multi-accelerator Platforms.

Steven Colleman, Arne Symons, Victor J. B. Jung, Marian Verhelst

Proceedings of the 25th International Symposium on Quality Electronic Design, 2024

2023

Stream: A Modeling Framework for Fine-grained Layer Fusion on Multi-core DNN Accelerators.

Arne Symons, Linyan Mei, Steven Colleman, Pouya Houshmand, Sebastian Karl, Marian Verhelst

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2023

DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling.

Linyan Mei, Koen Goetschalckx, Arne Symons, Marian Verhelst

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2023

Genetic Algorithm-based Framework for Layer-Fused Scheduling of Multiple DNNs on Multi-core Systems.

Sebastian Karl, Arne Symons, Nael Fasfous, Marian Verhelst

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

Hardware-aware NAS by Genetic Optimisation with a Design Space Exploration Simulator.

Lotte Hendrickx, Arne Symons, Wiebe Van Ranst, Marian Verhelst, Toon Goedemé

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

SALSA: Simulated Annealing based Loop-Ordering Scheduler for DNN Accelerators.

Victor J. B. Jung, Arne Symons, Linyan Mei, Marian Verhelst, Luca Benini

Proceedings of the 5th IEEE International Conference on Artificial Intelligence Circuits and Systems, 2023

2022

DeFiNES: A DSE Framework Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators.

Linyan Mei, Koen Goetschalckx, Arne Symons, Marian Verhelst

Dataset, November, 2022

Towards Heterogeneous Multi-core Accelerators Exploiting Fine-grained Scheduling of Layer-Fused Deep Neural Networks.

Arne Symons, Linyan Mei, Steven Colleman, Pouya Houshmand, Sebastian Karl, Marian Verhelst

CoRR, 2022

2021

LOMA: Fast Auto-Scheduling on DNN Accelerators through Loop-Order-based Memory Allocation.

Arne Symons, Linyan Mei, Marian Verhelst

Proceedings of the 3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, 2021