| 書(shū)目名稱 | User-Defined Tensor Data Analysis |
| 編輯 | Bin Dong,Kesheng Wu,Suren Byna |
| 視頻video | http://file.papertrans.cn/945/944518/944518.mp4 |
| 概述 | FasTensor can achieve multiple orders of magnitude speedup over Spark and other peer systems in executing big data analysis operations.FasTensor makes programming for data analysis operations at large |
| 叢書(shū)名稱 | SpringerBriefs in Computer Science |
| 圖書(shū)封面 |  |
| 描述 | The SpringerBrief introduces FasTensor, a powerful parallel data programming model developed for big data applications. This book also provides a user‘s guide for installing and using FasTensor. FasTensor enables users to easily express many data analysis operations, which may come from neural networks, scientific computing, or queries from traditional database management systems (DBMS). FasTensor frees users from all underlying and tedious data management tasks, such as data partitioning, communication, and parallel execution..This SpringerBrief gives a high-level overview of the state-of-the-art in parallel data programming model and a motivation for the design of FasTensor. It illustrates the FasTensor application programming interface (API) with an abundance of examples and two real use cases from cutting edge scientific applications. FasTensor can achieve multiple orders of magnitude speedup over? Spark and other peer systems in executing big data analysis operations. FasTensor makes programming for data analysis operations at large scale on supercomputers as productively and efficiently as possible. A complete reference of FasTensor includes its theoretical foundations, C++ i |
| 出版日期 | Book 2021 |
| 關(guān)鍵詞 | FasTensor; Stencil; Data Analysis; Scientific Data Management; Transform; Tensor; Array; Structural Localit |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-030-70750-7 |
| isbn_softcover | 978-3-030-70749-1 |
| isbn_ebook | 978-3-030-70750-7Series ISSN 2191-5768 Series E-ISSN 2191-5776 |
| issn_series | 2191-5768 |
| copyright | The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 |
|Archiver|手機(jī)版|小黑屋|
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