| 书目名称 | DataFlow Supercomputing Essentials |
| 副标题 | Algorithms, Applicat |
| 编辑 | Veljko Milutinovic,Milos Kotlar,Zoran Babovic |
| 视频video | |
| 概述 | Reviews the advantages of the DataFlow paradigm for supercomputing.Introduces the DataFlow programming model.Provides a selection of algorithm examples that illuminate the DataFlow paradigm |
| 丛书名称 | Computer Communications and Networks |
| 图书封面 |  |
| 描述 | This illuminating text/reference reviews the fundamentals of programming for effective DataFlow computing. The DataFlow paradigm enables considerable increases in speed and reductions in power consumption for supercomputing processes, yet the programming model requires a distinctly different approach. The algorithms and examples showcased in this book will help the reader to develop their understanding of the advantages and unique features of this methodology..This work serves as a companion title to .DataFlow Supercomputing Essentials: Research, Development and Education., which analyzes the latest research in this area, and the training resources available..Topics and features: presents an implementation of Neural Networks using the DataFlow paradigm, as an alternative to the traditional ControlFlow approach; discusses a solution to the three-dimensional Poisson equation, using the Fourier method and DataFlow technology; examines how the performance of the Binary Search algorithm can be improved through implementation on a DataFlow architecture; reviews the different way of thinking required to best configure the DataFlow engines for the processing of data in space flowing throug |
| 出版日期 | Book 2017 |
| 关键词 | DataFlow; Big Data; Supercomputing; Field-programmable gate array; Neural networks |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-66125-4 |
| isbn_softcover | 978-3-319-88183-6 |
| isbn_ebook | 978-3-319-66125-4Series ISSN 1617-7975 Series E-ISSN 2197-8433 |
| issn_series | 1617-7975 |
| copyright | Springer International Publishing AG 2017 |
发表于 2025-3-21 17:15:30
