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Hardware Aware Evolutionary Neural Architecture Search Using Representation Similarity Metric [PDF]

2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Hardware-aware Neural Architecture Search (HW-NAS) is a technique used to automatically design the architecture of a neural network for a specific task and target hardware. However, evaluating the performance of candidate architectures is a key challenge in HW-NAS, as it requires significant computational resources.
Nilotpal Sinha, Anis Kacem
exaly   +7 more sources

Multi-Objective Hardware Aware Neural Architecture Search Using Hardware Cost Diversity [PDF]

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Hardware-aware Neural Architecture Search approaches (HW-NAS) automate the design of deep learning architectures, tailored specifically to a given target hardware platform. Yet, these techniques demand substantial computational resources, primarily due to the expensive process of assessing the performance of identified architectures.
Nilotpal Sinha, Anis Kacem
exaly   +9 more sources

One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search [PDF]

Proceedings of the ACM on Measurement and Analysis of Computing Systems, 2021
Convolutional neural networks (CNNs) are used in numerous realworld applications such as vision-based autonomous driving and video content analysis.
Shaolei Ren, Yiyu Shi, Weiwen Jiang
exaly   +5 more sources

Fast Hardware-Aware Neural Architecture Search [PDF]

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020
Designing accurate and efficient convolutional neural architectures for vast amount of hardware is challenging because hardware designs are complex and diverse. This paper addresses the hardware diversity challenge in Neural Architecture Search (NAS).
Yunxin Liu, Wenwu Zhu, Yuqing Yang
exaly   +4 more sources

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Pareto Rank Surrogate Model for Hardware-Aware Neural Architecture Search

2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2022
Hamza Ouarnoughi, Smail Niar, Hadjer Benmeziane   +2 more
exaly   +3 more sources

Hardware-Aware Neural Architecture Search With Segmentation-Based Selection

2022 5th International Conference on Information and Computer Technologies (ICICT), 2022
Taehee Jeong, Elliott Delaye
exaly   +2 more sources

An Affordable Hardware-Aware Neural Architecture Search for Deploying Convolutional Neural Networks on Ultra-Low-Power Computing Platforms

Hardware-aware neural architecture search (HW-NAS) allows the integration of convolutional neural networks (CNNs) in microcontrollers devices by automatically designing neural architectures that can fit prearranged hardware constraints. However, state-of-
Edoardo Ragusa, Paolo Gastaldo, Antonio Frisoli   +2 more
exaly   +2 more sources

Hardware-Aware Neural Architecture Search for Memory Constrained Embedded Neural Networks Accelerators

2025 IEEE 7th International Conference on Artificial Intelligence Circuits and Systems (AICAS)
Vincent Huard
exaly   +3 more sources

Hardware-Aware Zero-Shot Neural Architecture Search

2023 18th International Conference on Machine Vision and Applications (MVA), 2023
Yoshihama, Yutaka, Yadani, Kenichi, Isobe, Shota   +2 more
openaire   +2 more sources

SNAS: Fast Hardware-Aware Neural Architecture Search Methodology

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022
Jaeseong Lee 0002, Jungsub Rhim, Duseok Kang, Soonhoi Ha   +3 more
openaire   +1 more source