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Mesh-TensorFlow

2 papers tagged archive 2025-07-28

Introduced by Noam Shazeer et al. in Mesh-TensorFlow: Deep Learning for Supercomputers

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Mesh-TensorFlow is a language for specifying a general class of distributed tensor computations. Where data-parallelism can be viewed as splitting tensors and operations along the "batch" dimension, in Mesh-TensorFlow, the user can specify any tensor dimensions to be split across any dimensions of a multi-dimensional mesh of processors. A MeshTensorFlow graph compiles into a SPMD program consisting of parallel operations coupled with collective communication primitives such as Allreduce.

PaperSource

Papers archive 2025-07-28

2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

6 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Deep Learning1
GPU1
Language Modeling1
Language Modelling1
Medical Image Analysis1
Vocal Bursts Intensity Prediction1

Usage over time archive 2025-07-28

Papers per year tagged with Mesh-TensorFlow: 2018 to 2019, peak 1 1 0 2018: 1 paper 2018 2019: 1 paper 2019
Papers per year the archive tags with this method, by the paper's archive date (2 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Intra-Layer ParallelModel Parallel MethodsDistributed Methods

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