{"url":"/method/pytorch-ddp","slug":"pytorch-ddp","name":"PyTorch DDP","full_name":"PyTorch DDP","full_name_withheld":false,"description_markdown":"**PyTorch DDP** (Distributed Data Parallel) is a distributed data parallel implementation for PyTorch. To guarantee mathematical equivalence, all replicas start from the same initial values for model parameters and synchronize gradients to keep parameters consistent across training iterations. To minimize the intrusiveness, the implementation exposes the same forward API as the user model, allowing applications to seamlessly replace subsequent occurrences of a user model with the distributed data parallel model object with no additional code changes. Several techniques are integrated into the design to deliver high-performance training, including bucketing gradients, overlapping communication with computation, and skipping synchronization.","description_state":"present","introduced_year":null,"introduced_by":{"title":"PyTorch Distributed: Experiences on Accelerating Data Parallel Training","paper":"/paper/pytorch-distributed-experiences-on","first_author":"Shen Li","n_authors":11,"url_abs":null,"archive_paper_url":"https://paperswithcode.com/paper/pytorch-distributed-experiences-on"},"source":{"url":"https://arxiv.org/abs/2006.15704v1","title":"PyTorch Distributed: Experiences on Accelerating Data Parallel Training","url_on_a_paper_host":true},"code_snippet_url":null,"code_snippet_url_on_a_code_host":false,"categories":[{"area":"General","area_id":"general","collection":"Replicated Data Parallel","url":"/methods/category/replicated-data-parallel","pwc_aliases":[]},{"area":"General","area_id":"general","collection":"Data Parallel Methods","url":"/methods/category/data-parallel-methods","pwc_aliases":[]},{"area":"General","area_id":"general","collection":"Distributed Methods","url":"/methods/category/distributed-methods","pwc_aliases":[]}],"n_papers_tagged":3,"archive_num_papers":3,"papers_newest_first":[{"paper":"/paper/advanced-language-model-based-translator-for","title":"Advanced Language Model-based Translator for English-Vietnamese Translation","date":"2024-05-27","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/kohtd-kazakh-offline-handwritten-text-dataset","title":"KOHTD: Kazakh Offline Handwritten Text Dataset","date":"2021-09-22","arxiv_id":"2110.04075","n_code_links":1,"syntology":null},{"paper":"/paper/pytorch-distributed-experiences-on","title":"PyTorch Distributed: Experiences on Accelerating Data Parallel Training","date":"2020-06-28","arxiv_id":"2006.15704","n_code_links":3,"syntology":{"ran":8,"of":12,"unverified":4,"pointer_only":3}}],"papers_shown":3,"tasks":[{"task":"/task/htr","name":"HTR","papers":1},{"task":"/task/handwriting-recognition","name":"Handwriting Recognition","papers":1},{"task":"/task/handwritten-text-recognition","name":"Handwritten Text Recognition","papers":1},{"task":"/task/language-modeling","name":"Language Modeling","papers":1},{"task":"/task/language-modelling","name":"Language Modelling","papers":1},{"task":"/task/machine-translation","name":"Machine Translation","papers":1},{"task":"/task/translation","name":"Translation","papers":1}],"tasks_shown":7,"n_tasks":7,"usage_by_year":[{"year":"2020","papers":1},{"year":"2021","papers":1},{"year":"2024","papers":1}],"row_source":"methods_table","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/pytorch-ddp"},"syntology_read_at":"2026-09-25T09:33:49+00:00"}