TY - CHAP
T1 - In Situ Wavelet Compression on Supercomputers for Post Hoc Exploration
AU - Li, Shaomeng
AU - Clyne, John
AU - Childs, Hank
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - Wavelet compression is a popular approach for reducing data size while maintaining high data integrity. This chapter considers how wavelet compression can be used for data visualization and post hoc exploration on supercomputers. There are three major parts in this chapter. The first part describes the basics of wavelet transforms, which are essential signal transformations in a wavelet compression pipeline, and how their properties can be used for data compression. The second part analyzes the efficacy of wavelet compression on scientific data, with a focus on analyses involving scientific visualizations. The third part evaluates how well wavelet compression fits in an in situ workflow on supercomputers. After reading this chapter, readers should have a high-level understanding of how wavelet compression works, as well as its efficacy for in situ compression and post hoc exploration.
AB - Wavelet compression is a popular approach for reducing data size while maintaining high data integrity. This chapter considers how wavelet compression can be used for data visualization and post hoc exploration on supercomputers. There are three major parts in this chapter. The first part describes the basics of wavelet transforms, which are essential signal transformations in a wavelet compression pipeline, and how their properties can be used for data compression. The second part analyzes the efficacy of wavelet compression on scientific data, with a focus on analyses involving scientific visualizations. The third part evaluates how well wavelet compression fits in an in situ workflow on supercomputers. After reading this chapter, readers should have a high-level understanding of how wavelet compression works, as well as its efficacy for in situ compression and post hoc exploration.
UR - https://www.scopus.com/pages/publications/85130094241
U2 - 10.1007/978-3-030-81627-8_3
DO - 10.1007/978-3-030-81627-8_3
M3 - Chapter
AN - SCOPUS:85130094241
T3 - Mathematics and Visualization
SP - 37
EP - 59
BT - Mathematics and Visualization
PB - Springer Science and Business Media Deutschland GmbH
ER -