Linghe Kong,
Linghe (Research Professor, Shanghai Jiao Tong University, China) Kong,
Tian Huang,
Tian (Research Associate, Astrophysics Group, University of Cambridge, UK) Huang,
Yongxin Zhu,
Yongxin (Professor, Shanghai Advanced Research Institute, Chinese Academy of Sciences, China) Zhu,
Shenghua Yu,
Shenghua (Associate Professor, National Astronomical Observatories, Chinese Academy of Sciences, China) Yu
e.a.
Big Data in Astronomy
Scientific Data Processing for Advanced Radio Telescopes
Paperback Engels 2020 9780128190845Levertijd ongeveer 9 werkdagen
Gratis verzonden
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
ISBN13:9780128190845
Taal:Engels
Bindwijze:Paperback
Aantal pagina's:438
Uitgever:Elsevier Science
Hoofdrubriek:Wetenschap en techniek, Computer en informatica
Lezersrecensies
Wees de eerste die een lezersrecensie schrijft!
Inhoudsopgave
Part A: Fundamentals
Chapter 1: Introduction of Radio Astronomy
Chapter 2: Fundamentals of Big Data in Radio Astronomy
Part B: Big Data Processing
Chapter 3: Pre-processing Pipeline on FPGA
Chapter 4: Real-time stream processing in radio astronomy
Chapter 5: Digitization, Channelization and Packeting
Chapter 6: Processing Data of Correlation on GPU
Chapter 7: Data Calibration for single dish radio telescope
Chapter 8: Imaging Algorithm Optimization for Scale-out Processing
Part C: Computing Technologies
Chapter 9: Execution Framework Technology
Chapter 10: Application Design For Execution Framework
Chapter 11: Heterogeneous Computing Platform for Backend Computing Tasks
Chapter 12: High Performance Computing for Astronomical Big Data
Chapter 13: Spark and Dask Performance Analysis Based on ARL Image Library
Chapter 14: Applications of Artificial Intelligence in Astrnomical Big Data
Part D: Future Developments
Chapter 15: Mapping the Universe with 21cm Observations
Chapter 1: Introduction of Radio Astronomy
Chapter 2: Fundamentals of Big Data in Radio Astronomy
Part B: Big Data Processing
Chapter 3: Pre-processing Pipeline on FPGA
Chapter 4: Real-time stream processing in radio astronomy
Chapter 5: Digitization, Channelization and Packeting
Chapter 6: Processing Data of Correlation on GPU
Chapter 7: Data Calibration for single dish radio telescope
Chapter 8: Imaging Algorithm Optimization for Scale-out Processing
Part C: Computing Technologies
Chapter 9: Execution Framework Technology
Chapter 10: Application Design For Execution Framework
Chapter 11: Heterogeneous Computing Platform for Backend Computing Tasks
Chapter 12: High Performance Computing for Astronomical Big Data
Chapter 13: Spark and Dask Performance Analysis Based on ARL Image Library
Chapter 14: Applications of Artificial Intelligence in Astrnomical Big Data
Part D: Future Developments
Chapter 15: Mapping the Universe with 21cm Observations
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