Model-less Is the Best Model: Generating Pure Code Implementations to Replace On-Device DL Models
Author:
Affiliation:
1. Monash University, Clayton, Australia
2. Beihang University, Beijing, China
3. CSIRO's Data61, Clayton, Australia
4. TU Munich, Heilbronn, Germany
5. University of Newcastle, Callaghan, Australia
Funder
Australian Research Council
National Natural Science Foundation of China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3650212.3652119
Reference44 articles.
1. 2022. m2cgen. https://github.com/BayesWitnesses/m2cgen
2. 2022. tf2onnx - Convert TensorFlow Keras Tensorflow.js and Tflite models to ONN. https://github.com/onnx/tensorflow-onnx
3. 2024. llama.cpp. https://github.com/ggerganov/llama.cpp
4. Martín Abadi Ashish Agarwal Paul Barham Eugene Brevdo Zhifeng Chen Craig Citro Greg S. Corrado Andy Davis Jeffrey Dean Matthieu Devin Sanjay Ghemawat Ian Goodfellow Andrew Harp Geoffrey Irving Michael Isard Yangqing Jia Rafal Jozefowicz Lukasz Kaiser Manjunath Kudlur Josh Levenberg Dandelion Mané Rajat Monga Sherry Moore Derek Murray Chris Olah Mike Schuster Jonathon Shlens Benoit Steiner Ilya Sutskever Kunal Talwar Paul Tucker Vincent Vanhoucke Vijay Vasudevan Fernanda Viégas Oriol Vinyals Pete Warden Martin Wattenberg Martin Wicke Yuan Yu and Xiaoqiang Zheng. 2015. TensorFlow: Large-Scale Machine Learning on Heterogeneous Systems. https://www.tensorflow.org/ Software available from tensorflow.org
5. Simin Chen, Hamed Khanpour, Cong Liu, and Wei Yang. 2022. Learning to reverse dnns from ai programs automatically. In AAAI Conference on Artificial Intelligence.
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