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ORCIDCODAI 2023: Hamburg, Germany
- Proceedings of the 2023 Workshop on Compilers, Deployment, and Tooling for Edge AI, CODAI 2023, Hamburg, Germany, 21 September 2023. ACM 2023
- Yao Lu
, Hiram Rayo Torres Rodriguez, Sebastian Vogel, Nick van de Waterlaat, Pavol Jancura:
Scaling Up Quantization-Aware Neural Architecture Search for Efficient Deep Learning on the Edge. 1-5 - Samira Ahmadifarsani, Rafael Stahl, Philipp van Kempen, Daniel Mueller-Gritschneder, Ulf Schlichtmann:
Towards Rapid Exploration of Heterogeneous TinyML Systems using Virtual Platforms and TVM's UMA. 6-10 - Endri Bezati:
ART: An Actor transition systems RunTime for enabling efficient partitioning of neural network graphs. 11-15 - Matheus Fellype Ferraz, Birte Kristina Friesel, Olaf Spinczyk:
Pros and Cons of Executable Neural Networks for Deeply Embedded Systems. 16-20 - Federico Nicolás Peccia, Oliver Bringmann:
Integration of a systolic array based hardware accelerator into a DNN operator auto-tuning framework. 21-26 - Bernhard Vogginger, Florian Kelber, Shambhavi Balamuthu Sampath, Johannes Partzsch, Christian Mayr:
Performance models and energy-optimal scheduling of DNNs on many-core hardware with dynamic power management. 27-31 - Philipp van Kempen, Rafael Stahl, Daniel Mueller-Gritschneder, Ulf Schlichtmann:
MLonMCU: TinyML Benchmarking with Fast Retargeting. 32-36 - Chen Liu, Matthias Jobst, Liyuan Guo, Xinyue Shi, Johannes Partzsch, Christian Mayr:
Deploying Machine Learning Models to Ahead-of-Time Runtime on Edge Using MicroTVM. 37-40 - Lotfi Abdelkrim Mecharbat, Hadjer Benmeziane, Hamza Ouarnoughi, Smaïl Niar:
HyT-NAS: Hybrid Transformers Neural Architecture Search for Edge Devices. 41-45
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