Training and Serving System of Foundation Models: A Comprehensive Survey

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Zhou, Jiahang, et al. “Training and Serving System of Foundation Models: A Comprehensive Survey”. IEEE Open Journal of the Computer Society, vol. 5, 2024, pp. 107-19, https://doi.org/10.1109/ojcs.2024.3380828.
Zhou, J., Chen, Y., Hong, Z., Chen, W., Yu, Y., Zhang, T., Wang, H., Zhang, C., & Zheng, Z. (2024). Training and Serving System of Foundation Models: A Comprehensive Survey. IEEE Open Journal of the Computer Society, 5, 107-119. https://doi.org/10.1109/ojcs.2024.3380828
Zhou J, Chen Y, Hong Z, Chen W, Yu Y, Zhang T, et al. Training and Serving System of Foundation Models: A Comprehensive Survey. IEEE Open Journal of the Computer Society. 2024;5:107-19.
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Refrences
Title Journal Journal Categories Citations Publication Date
G10: Enabling an efficient unified GPU memory and storage architecture with smart tensor migrations 2023
Checkmate: Breaking the memory wall with optimal tensor rematerialization 2022
Accelerating distributed MoE training and inference with Lina 2023
SmartMoE: Efficiently training sparsely-activated models through combining offline and online parallelization 2023
Fast inference from transformers via speculative decoding 2023