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MG-WFBP: Efficient Data Communication for Distributed Synchronous SGD Algorithms., and . CoRR, (2018)Communication-Efficient Distributed Deep Learning with Merged Gradient Sparsification on GPUs., , , , , , and . INFOCOM, page 406-415. IEEE, (2020)Mixed Precision Method for GPU-based FFT., , and . CSE, page 580-586. IEEE Computer Society, (2011)Reliable and Efficient In-Memory Fault Tolerance of Large Language Model Pretraining., , , , , , , , , and . CoRR, (2023)Towards Scalable Distributed Training of Deep Learning on Public Cloud Clusters., , , , , , , , , and 14 other author(s). MLSys, mlsys.org, (2021)Communication-Efficient Distributed Deep Learning: A Comprehensive Survey., , , , and . CoRR, (2020)Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format., , and . ICPADS, page 19-26. IEEE, (2020)PipeMoE: Accelerating Mixture-of-Experts through Adaptive Pipelining., , , and . INFOCOM, page 1-10. IEEE, (2023)Accelerating Distributed K-FAC with Efficient Collective Communication and Scheduling., , and . INFOCOM, page 1-10. IEEE, (2023)Layer-Wise Adaptive Gradient Sparsification for Distributed Deep Learning with Convergence Guarantees., , , , and . ECAI, volume 325 of Frontiers in Artificial Intelligence and Applications, page 1467-1474. IOS Press, (2020)