5 papers · 1 filter
Compilation and Execution of an Embeddable YOLO-NAS on the VTA
Anthony Faure-Gignoux, Kevin Delmas, Adrien Gauffriau +1
Deploying complex Convolutional Neural Networks (CNNs) on FPGA-based accelerators is a promising way forward for safety-critical domains such as aeronautics. In a previous work, we…
Convolutions Predictable Offloading to an Accelerator: Formalization and Optimization
Benjamin Husson, Mohammed Belcaïd, Thomas Carle +1
Convolutional neural networks (CNNs) require a large number of multiply-accumulate (MAC) operations. To meet real-time constraints, they often need to be executed on specialized ac…
Open-source Stand-Alone Versatile Tensor Accelerator
Anthony Faure-Gignoux, Kevin Delmas, Adrien Gauffriau +1
Machine Learning (ML) applications demand significant computational resources, posing challenges for safety-critical domains like aeronautics. The Versatile Tensor Accelerator (VTA…
COOK Access Control on an embedded Volta GPU
Benjamin Lesage, Frédéric Boniol, Claire Pagetti
The last decade has seen the emergence of a new generation of multi-core in response to advances in machine learning, and in particular Deep Neural Network (DNN) training and infer…
Towards the Certification of Hybrid Architectures: Analysing Interference on Hardware Accelerators through PML
Benjamin Lesage, Frédéric Boniol, Kevin Delmas +3
The emergence of Deep Neural Network (DNN) and machine learning-based applications paved the way for a new generation of hybrid hardware platforms. Hybrid platforms embed several c…