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Titlebook: High Performance Computing; 33rd International C Rio Yokota,Michèle Weiland,Carsten Trinitis Conference proceedings 2018 Springer Internati

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發(fā)表于 2025-3-21 16:04:17 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱High Performance Computing
副標題33rd International C
編輯Rio Yokota,Michèle Weiland,Carsten Trinitis
視頻videohttp://file.papertrans.cn/427/426289/426289.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: High Performance Computing; 33rd International C Rio Yokota,Michèle Weiland,Carsten Trinitis Conference proceedings 2018 Springer Internati
描述.This book constitutes the refereed proceedings of the 33rd International Conference, ISC High Performance 2018, held in Frankfurt, Germany, in June 2018...The 20 revised full papers presented in this book were carefully reviewed and selected from 81 submissions. The papers cover the following topics: Resource Management and Energy Efficiency; Performance Analysis and Tools; Exascale Networks; Parallel Algorithms..
出版日期Conference proceedings 2018
關鍵詞Artificial intelligence; Computer architectures; Dependable and fault-tolerant systems and networks; Di
版次1
doihttps://doi.org/10.1007/978-3-319-92040-5
isbn_softcover978-3-319-92039-9
isbn_ebook978-3-319-92040-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

書目名稱High Performance Computing影響因子(影響力)




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書目名稱High Performance Computing網(wǎng)絡公開度學科排名




書目名稱High Performance Computing被引頻次




書目名稱High Performance Computing被引頻次學科排名




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書目名稱High Performance Computing讀者反饋




書目名稱High Performance Computing讀者反饋學科排名




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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/h/image/426289.jpg
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Applicability of the ECM Performance Model to Explicit ODE Methods on Current Multi-core Processorsntation variants to support the variant selection. We investigate the accuracy of the prediction for different ODEs and different hardware platforms and show that the prediction is able to reliably select a set of fast variants and, thus, to limit the search space for possible later empirical tuning
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Machine Learning Based Parallel I/O Predictive Modeling: A Case Study on Lustre File Systemsed models are better at prediction when compared with application-partitioned or unpartitioned models. We highlight modeling techniques that are robust to the outliers that can occur in production parallel file systems. Using the developed metrics and modeling approach, we provide insights into the
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t und übersichtlich: Alles in einem.Die richtige Wahl: für K.Alle Grundlagen der An?sthesie, Intensiv- und Notfallmedizin sowie der Schmerztherapie inkl. aktueller Reanimationsleitlinien. Komplett überarbeitet, aber nach wie vor knapp, praxisnah und übersichtlich. Das gesamte Fachwissen auf aktuelle
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