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Parallel Backpropagation Neural Network for Big Data Processing on Many-Core Platform
| Content Provider | Scilit |
|---|---|
| Author | Li, Boyang Liu, Chen |
| Copyright Year | 2017 |
| Description | With the rapid data scale growth, machine-learning algorithms are widely adopted to deal with big data. It naturally becomes the focus of researchers and software developers how to run such algorithms efficiently on modern many-core platforms. In this chapter, two unique hardware platforms, Intel® Single-Chip Cloud Computer (SCC) and Intel® Xeon® Phi™ coprocessor, are employed to accelerate the backpropagation (BP) neural network and lead to a better performance for data processing. Furthermore, we also explored dynamic voltage and frequency scaling (DVFS) on the many-core platform in searching of the suitable configuration to aid the processing of big data when the power/energy savings need to be taken into consideration. Book Name: Big Data Management and Processing |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2015-0-77928-6&isbn=9781315154008&doi=10.1201/9781315154008-8&format=pdf |
| Ending Page | 172 |
| Page Count | 14 |
| Starting Page | 159 |
| DOI | 10.1201/9781315154008-8 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2017-05-19 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Big Data Management and Processing Computation Theory and Mathematics Neural Backpropagation Big Data Processing Intel Core Platforms |
| Content Type | Text |
| Resource Type | Chapter |
