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OneFlow at Scale: Architecting Parallel and Distributed Deep Learning Systems, (Paperback)
Item #: 267874993

OneFlow at Scale: Architecting Parallel and Distributed Deep Learning Systems, (Paperback)

Item #: 267874993

USD 55

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OneFlow at Scale: Architecting Parallel and Distributed Deep Learning Systems, (Paperback)
  • OneFlow at Scale: Architecting Parallel and Distributed Deep Learning Systems is a comprehensive guide to building and operating large-scale deep learning systems with OneFlow. It explores the framework's core design principles, its architecture, and the motivations behind its evolution in the context of modern distributed machine learning. Through a clear comparison with platforms such as TensorFlow, PyTorch, Horovod, and MXNet, the book explains how OneFlow addresses the challenges of training increasingly large models across cloud, cluster, and high-performance computing environments. The book provides a deep technical treatment of the full OneFlow stack, including scheduling, resource management, data pipelines, elasticity, and fault tolerance. It presents the major forms of parallelism-data, model, pipeline, and hybrid approaches-along with device placement, load balancing, synchronization strategies, and communication protocols that drive efficient distributed training. Readers will gain both the formal understanding and practical insight needed to maximize throughput, scalability, and resilience in demanding production and research workloads. Beyond system architecture, the book bridges theory and practice with hands-on guidance for deployment, monitoring, debugging, security, and extensibility across heterogeneous backends. It also includes real-world case studies in vision, NLP, and multimodal learning, as well as emerging topics such as federated learning, green AI, and compiler integration. Designed for engineers, researchers, and technical leaders, this volume serves as an essential reference for mastering scalable parallel and distributed deep learning with OneFlow.
Book formatPaperback
Fiction/nonfictionNon-Fiction
GenreComputing & Internet
Publication dateSeptember, 2026
Pages236
SubgenreGeneral
Series titleNo Series
Edition1
PublisherAmazon Digital Services LLC - Kdp
Original languagesEnglish
LanguageEnglish
Educational levelHigher
Is collectibleN
Recording time0 min
Retail packagingSingle Piece
Assembled product dimensions (l x w x h)6.00 x 0.50 x 9.00 in (15.2 x 1.3 x 22.9 cm)
Assembled product weight0.71 lb (320 grams)
Bisac subject headingComputers

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OneFlow at Scale: Architecting Parallel and Distributed Deep Learning Systems, (Paperback)

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