SAFA : a semi-asynchronous protocol for fast federated learning with low overhead
| العنوان: | SAFA : a semi-asynchronous protocol for fast federated learning with low overhead |
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| المؤلفون: | Weiwei Lin, Carsten Maple, Ligang He, Wentai Wu, Rui Mao, Stephen A. Jarvis |
| بيانات النشر: | IEEE, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | FOS: Computer and information sciences, Computer Science - Machine Learning, Computer science, Distributed computing, media_common.quotation_subject, 02 engineering and technology, Q1, Machine Learning (cs.LG), Theoretical Computer Science, Data modeling, QA76, Resource (project management), Convergence (routing), 0202 electrical engineering, electronic engineering, information engineering, Quality (business), Duration (project management), Protocol (object-oriented programming), media_common, Distributed database, 020202 computer hardware & architecture, Computer Science - Distributed, Parallel, and Cluster Computing, Computational Theory and Mathematics, Hardware and Architecture, Asynchronous communication, Distributed, Parallel, and Cluster Computing (cs.DC), Software |
| الوصف: | Federated learning (FL) has attracted increasing attention as a promising approach to driving a vast number of end devices with artificial intelligence. However, it is very challenging to guarantee the efficiency of FL considering the unreliable nature of end devices while the cost of device-server communication cannot be neglected. In this paper, we propose SAFA, a semi-asynchronous FL protocol, to address the problems in federated learning such as low round efficiency and poor convergence rate in extreme conditions (e.g., clients dropping offline frequently). We introduce novel designs in the steps of model distribution, client selection and global aggregation to mitigate the impacts of stragglers, crashes and model staleness in order to boost efficiency and improve the quality of the global model. We have conducted extensive experiments with typical machine learning tasks. The results demonstrate that the proposed protocol is effective in terms of shortening federated round duration, reducing local resource wastage, and improving the accuracy of the global model at an acceptable communication cost. Comment: 16 pages, 8 figures |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 0018-9340 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0e740194f307d30c7c1fd9d14eb6746 http://wrap.warwick.ac.uk/136903/1/WRAP-safa-semi-asynchronous-protocol-fast-federated-learning-low-overhead-He-2020.pdf |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....e0e740194f307d30c7c1fd9d14eb6746 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 00189340 |
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