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Communication Quantization for Data-Parallel Training of Deep Neural Networks.

, , , and . MLHPC@SC, page 1-8. IEEE Computer Society, (2016)

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Parallelizing Graph Neural Networks via Matrix Compaction for Edge-Conditioned Networks., , , , , and . CCGRID, page 386-395. IEEE, (2022)Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models., , , , , , , , , and 2 other author(s). Int. J. High Perform. Comput. Appl., (2021)Accelerating eigenvector and pseudospectra computation using blocked multi-shift triangular solves., and . CoRR, (2016)Improving Strong-Scaling of CNN Training by Exploiting Finer-Grained Parallelism., , , , , and . IPDPS, page 210-220. IEEE, (2019)Learning Interpretable Models Through Multi-Objective Neural Architecture Search., , and . CoRR, (2021)Communication Quantization for Data-Parallel Training of Deep Neural Networks., , , and . MLHPC@SC, page 1-8. IEEE Computer Society, (2016)SUPER: SUb-Graph Parallelism for TransformERs., , , , , , and . IPDPS, page 629-638. IEEE, (2021)Channel and filter parallelism for large-scale CNN training., , , , , and . SC, page 10:1-10:20. ACM, (2019)Parallelizing Training of Deep Generative Models on Massive Scientific Datasets., , , , , , , , , and 4 other author(s). CLUSTER, page 1-10. IEEE, (2019)