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Image Classification at Supercomputer Scale., , , , and . CoRR, (2018)Exploring the limits of Concurrency in ML Training on Google TPUs., , , , , , , , , and 9 other author(s). CoRR, (2020)Exploring the Limits of Concurrency in ML Training on Google TPUS., , , , , , and . MLSys, mlsys.org, (2021)GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding., , , , , , , , and . ICLR, OpenReview.net, (2021)GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism., , , , , , and . CoRR, (2018)GSPMD: General and Scalable Parallelization for ML Computation Graphs., , , , , , , , , and 6 other author(s). CoRR, (2021)Tree partition based parallel frequent pattern mining on shared memory systems., , , , , and . IPDPS, IEEE, (2006)AutoFDO: automatic feedback-directed optimization for warehouse-scale applications., , and . CGO, page 12-23. ACM, (2016)Taming hardware event samples for FDO compilation., , , , , , , and . CGO, page 42-52. ACM, (2010)Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling, , , , , , , , , and 81 other author(s). (2019)cite arxiv:1902.08295.