Linghe Kong,
Tian Huang,
Yongxin Zhu,
Shenghua Yu
e.a.
Elsevier Science
e druk, 2020
9780128190845
Big Data in Astronomy
Scientific Data Processing for Advanced Radio Telescopes
Specificaties
Paperback, blz.
|
Engels
Elsevier Science |
e druk, 2020
ISBN13: 9780128190845
Rubricering
Verwachte levertijd ongeveer 9 werkdagen
Samenvatting
Big Data in Radio Astronomy: Scientific Data Processing for Advanced Radio Telescopes provides the latest research developments in big data methods and techniques for radio astronomy. Providing examples from such projects as the Square Kilometer Array (SKA), the world’s largest radio telescope that generates over an Exabyte of data every day, the book offers solutions for coping with the challenges and opportunities presented by the exponential growth of astronomical data. Presenting state-of-the-art results and research, this book is a timely reference for both practitioners and researchers working in radio astronomy, as well as students looking for a basic understanding of big data in astronomy.
Specificaties
Inhoudsopgave
<p>Part A: Fundamentals</p> <p>Chapter 1: Introduction of Radio Astronomy</p> <p>Chapter 2: Fundamentals of Big Data in Radio Astronomy</p> <p>Part B: Big Data Processing</p> <p>Chapter 3: Pre-processing Pipeline on FPGA</p> <p>Chapter 4: Real-time stream processing in radio astronomy</p> <p>Chapter 5: Digitization, Channelization and Packeting </p> <p>Chapter 6: Processing Data of Correlation on GPU</p> <p>Chapter 7: Data Calibration for single dish radio telescope</p> <p>Chapter 8: Imaging Algorithm Optimization for Scale-out Processing</p> <p>Part C: Computing Technologies </p> <p>Chapter 9: Execution Framework Technology</p> <p>Chapter 10: Application Design For Execution Framework</p> <p>Chapter 11: Heterogeneous Computing Platform for Backend Computing Tasks</p> <p>Chapter 12: High Performance Computing for Astronomical Big Data</p> <p>Chapter 13: Spark and Dask Performance Analysis Based on ARL Image Library</p> <p>Chapter 14: Applications of Artificial Intelligence in Astrnomical Big Data</p> <p>Part D: Future Developments </p> <p>Chapter 15: Mapping the Universe with 21cm Observations</p>