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Densifying Assumed-sparse Tensors: Improving Memory Efficiency and MPI Collective Performance during Tensor Accumulation for Parallelized Training of Neural Machine Translation Models., , , , , , , , , and 4 other author(s). CoRR, (2019)NAS Parallel Benchmarks for GPGPUs Using a Directive-Based Programming Model., , , , and . LCPC, volume 8967 of Lecture Notes in Computer Science, page 67-81. Springer, (2014)Exploring Programming Multi-GPUs Using OpenMP and OpenACC-Based Hybrid Model., , and . IPDPS Workshops, page 1169-1176. IEEE, (2013)Implementing the OpenACC Data Model., , , , , , and . IPDPS Workshops, page 662-672. IEEE Computer Society, (2017)An Analytical Model-Based Auto-tuning Framework for Locality-Aware Loop Scheduling., , , and . ISC, volume 9697 of Lecture Notes in Computer Science, page 3-20. Springer, (2016)Deep Learning at Scale on NVIDIA V100 Accelerators., , and . PMBS@SC, page 23-32. IEEE, (2018)Filesystem Aware Scalable I/O Framework for Data-Intensive Parallel Applications., , and . IPDPS Workshops, page 2007-2014. IEEE, (2013)The OpenACC data model: Preliminary study on its major challenges and implementations., , , , , , and . Parallel Comput., (2018)Accelerating Kirchhoff migration on GPU using directives., , , , and . WACCPD@SC, page 37-46. IEEE Computer Society, (2014)A Validation Testsuite for OpenACC 1.0., , , , and . IPDPS Workshops, page 1407-1416. IEEE Computer Society, (2014)