학술논문

Understanding Performance-Quality Trade-offs in Scientific Visualization Workflows with Lossy Compression
Document Type
Conference
Source
2019 IEEE/ACM 5th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-5) DRBSD-5 Data Analysis and Reduction for Big Scientific Data (DRBSD-5), 2019 IEEE/ACM 5th International Workshop on. :1-7 Nov, 2019
Subject
Computing and Processing
Data visualization
Data models
Tools
Measurement
Concurrent computing
Graphics processing units
Bandwidth
reduction
visualization
adios
sz
zfp
mgard
Language
Abstract
The cost of I/O is a significant challenge on current supercomputers, and the trend is likely to continue into the foreseeable future. This challenge is amplified in scientific visualization because of the requirement to consume large amounts of data before processing can begin. Lossy compression has become an important technique in reducing the cost of performing I/O. In this paper we consider the implications of using compressed data for visualization within a scientific workflow. We use visualization operations on simulation data that is reduced using three different state-of-the-art compression techniques. We study the storage efficiency and preservation of visualization features on the resulting compressed data, and draw comparisons between the three techniques used. Our contributions can help inform both scientists and researchers in the use and design of compression techniques for preservation of important visualization details.