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Fast and accurate variable batch size convolution neural network training on large scale distributed systems.

, , , and . Concurr. Comput. Pract. Exp., (2022)

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AGCM3D: A Highly Scalable Finite-Difference Dynamical Core of Atmospheric General Circulation Model Based on 3D Decomposition., , , , , , and . ICPADS, page 355-364. IEEE, (2018)Communication Lower Bounds of Convolutions in CNNs., , and . SPAA, page 591-593. ACM, (2020)AGCM-3DLF: Accelerating Atmospheric General Circulation Model via 3-D Parallelization and Leap-Format., , , , , , , , , and . IEEE Trans. Parallel Distributed Syst., 34 (3): 766-780 (March 2023)SI on parallel system and algorithm optimization., and . CCF Trans. High Perform. Comput., 5 (3): 229-230 (September 2023)S-EnKF: co-designing for scalable ensemble Kalman filter., , , , and . PPoPP, page 15-26. ACM, (2019)Multilevel correction for collocation solutions of Volterra integral equations with proportional delays., and . Adv. Comput. Math., 39 (3-4): 611-644 (2013)Fast and accurate variable batch size convolution neural network training on large scale distributed systems., , , and . Concurr. Comput. Pract. Exp., (2022)I/O Lower Bounds for Auto-tuning of Convolutions in CNNs., , and . CoRR, (2020)Trade-offs between computation, communication, and synchronization in stencil-collective alternate update., and . CCF Trans. High Perform. Comput., 1 (2): 144-160 (2019)MegTaiChi: dynamic tensor-based memory management optimization for DNN training., , , , , , , , and . ICS, page 25:1-25:13. ACM, (2022)