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Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation: 21st Smoky Mountains Comp, Nichols Jeffrey, Maccabe Arthur `barney`, Nutaro James


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Цена: 12577.00р.
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При оформлении заказа до: 2025-07-28
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Автор: Nichols Jeffrey, Maccabe Arthur `barney`, Nutaro James
Название:  Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation: 21st Smoky Mountains Comp
ISBN: 9783030964979
Издательство: Springer
Классификация:





ISBN-10: 3030964973
Обложка/Формат: Paperback
Страницы: 484
Вес: 0.67 кг.
Дата издания: 10.04.2022
Серия: Communications in computer and information science
Язык: English
Издание: 1st ed. 2022
Иллюстрации: 160 illustrations, color; 11 illustrations, black and white; xv, 467 p. 171 illus., 160 illus. in color.
Размер: 23.39 x 15.60 x 2.46 cm
Читательская аудитория: Professional & vocational
Подзаголовок: 21st smoky mountains computational sciences and engineering, smc 2021, virtual event, october 18-20, 2021, revised selected papers
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book constitutes the revised selected papers of the 21st Smoky Mountains Computational Sciences and Engineering Conference, SMC 2021, held in Oak Ridge, TN, USA*, in October 2021. The 33 full papers and 3 short papers presented were carefully reviewed and selected from a total of 88 submissions. The papers are organized in topical sections of computational applications: converged HPC and artificial intelligence; advanced computing applications: use cases that combine multiple aspects of data and modeling; advanced computing systems and software: connecting instruments from edge to supercomputers; deploying advanced computing platforms: on the road to a converged ecosystem; scientific data challenges. *The conference was held virtually due to the COVID-19 pandemic.
Дополнительное описание: Computational Applications: Converged HPC and Artificial Intelligence.- Advanced Computing Applications: Use Cases that Combine Multiple Aspects of Data and Modeling.- Advanced Computing Systems and Software: Connecting Instruments from Edge to Supercompu



Driving Scientific and Engineering Discoveries Through the Convergence of Hpc, Big Data and AI: 17th Smoky Mountains Computational Sciences and Engine

Автор: Nichols Jeffrey, Verastegui Becky, Maccabe Arthur `barney`
Название: Driving Scientific and Engineering Discoveries Through the Convergence of Hpc, Big Data and AI: 17th Smoky Mountains Computational Sciences and Engine
ISBN: 3030633926 ISBN-13(EAN): 9783030633929
Издательство: Springer
Цена: 18167.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the revised selected papers of the 17th Smoky Mountains Computational Sciences and Engineering Conference, SMC 2020, held in Oak Ridge, TN, USA*, in August 2020.The 36 full papers and 1 short paper presented were carefully reviewed and selected from a total of 94 submissions.

Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation

Автор: Doug
Название: Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation
ISBN: 303123605X ISBN-13(EAN): 9783031236051
Издательство: Springer
Рейтинг:
Цена: 12577.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the refereed proceedings of the 22nd Smoky Mountains Computational Sciences and Engineering Conference on Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, SMC 2022, held virtually, during August 23–25, 2022. The 24 full papers included in this book were carefully reviewed and selected from 74 submissions. They were organized in topical sections as follows: foundational methods enabling science in an integrated ecosystem; science and engineering applications requiring and motivating an integrated ecosystem; systems and software advances enabling an integrated science and engineering ecosystem; deploying advanced technologies for an integrated science and engineering ecosystem; and scientific data challenges.


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