Optimization and Deployment of CNNs at the Edge: The ALOHA Experience
Published in In the proceedings of Proceedings of the 16th ACM International Conference on Computing Frontiers, 2019
Recommended citation: Paolo Meloni, Daniela Loi, Paola Busia, Gianfranco Deriu, Andy Pimentel, Dolly Sapra, Todor Stefanov, Svetlana Minakova, Francesco Conti, Luca Benini, Maura Pintor, Battista Biggio, Bernhard Moser, Natalia Shepeleva, Nikos Fragoulis, Ilias Theodorakopoulos, Michael Masin, Francesca Palumbo, "Optimization and Deployment of CNNs at the Edge: The ALOHA Experience." In the proceedings of Proceedings of the 16th ACM International Conference on Computing Frontiers, 2019. https://doi.org/10.1145/3310273.3323435
Abstract:
Deep learning (DL) algorithms have already proved their effectiveness on a wide variety of application domains, including speech recognition, natural language processing, and image classification. To foster their pervasive adoption in applications where low latency, privacy issues and data bandwidth are paramount, the current trend is to perform inference tasks at the edge. This requires deployment of DL algorithms on low-energy and resource-constrained computing nodes, often heterogenous and parallel, that are usually more complex to program and to manage without adequate support and experience. In this paper, we present ALOHA, an integrated tool flow that tries to facilitate the design of DL applications and their porting on embedded heterogenous architectures. The proposed tool flow aims at automating different design steps and reducing development costs. ALOHA considers hardware-related variables and security, power efficiency, and adaptivity aspects during the whole development process, from pre-training hyperparameter optimization and algorithm configuration to deployment.
BibTeX:
@conference{10.1145/3310273.3323435,
author = {Meloni, Paolo and Loi, Daniela and Busia, Paola and Deriu, Gianfranco and Pimentel, Andy D. and Sapra, Dolly and Stefanov, Todor and Minakova, Svetlana and Conti, Francesco and Benini, Luca and Pintor, Maura and Biggio, Battista and Moser, Bernhard and Shepeleva, Natalia and Fragoulis, Nikos and Theodorakopoulos, Ilias and Masin, Michael and Palumbo, Francesca},
title = {Optimization and Deployment of CNNs at the Edge: The ALOHA Experience},
year = {2019},
isbn = {9781450366854},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3310273.3323435},
doi = {10.1145/3310273.3323435},
booktitle = {Proceedings of the 16th ACM International Conference on Computing Frontiers},
pages = {326–332},
numpages = {7},
keywords = {hardware accelerators, convolution neural networks, FPGAs},
location = {Alghero, Italy},
series = {CF ‘19}
}