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AccDP: Accelerated Data-Parallel Distributed DNN Training for Modern GPU-Based HPC Clusters., , , , and . HIPC, page 32-41. IEEE, (2022)Towards Architecture-aware Hierarchical Communication Trees on Modern HPC Systems., , , , , , , and . HiPC, page 272-281. IEEE, (2021)Highly Efficient Alltoall and Alltoallv Communication Algorithms for GPU Systems., , , , , and . IPDPS Workshops, page 24-33. IEEE, (2022)Designing High-Performance MPI Libraries with On-the-fly Compression for Modern GPU Clusters*., , , , , , and . IPDPS, page 444-453. IEEE, (2021)Efficient MPI-based Communication for GPU-Accelerated Dask Applications., , , and . CCGRID, page 277-286. IEEE, (2021)MPI-xCCL: A Portable MPI Library over Collective Communication Libraries for Various Accelerators., , , , , , and . SC Workshops, page 847-854. ACM, (2023)High-Performance Adaptive MPI Derived Datatype Communication for Modern Multi-GPU Systems., , , , and . HiPC, page 267-276. IEEE, (2019)NV-group: link-efficient reduction for distributed deep learning on modern dense GPU systems., , , , , and . ICS, page 6:1-6:12. ACM, (2020)Performance Evaluation of MPI Libraries on GPU-Enabled OpenPOWER Architectures: Early Experiences., , , and . ISC Workshops, volume 11887 of Lecture Notes in Computer Science, page 361-378. Springer, (2019)Communication Profiling and Characterization of Deep Learning Workloads on Clusters with High-Performance Interconnects., , , , and . Hot Interconnects, page 49-53. IEEE, (2019)