View-Dependent Data Prefetching for Interactive Visualization of Large-Scale 3D Scientific Data
- Authors
- Publication Date
- Nov 01, 2019
- Source
- University of Nebraska - Lincoln
- Keywords
- License
- Unknown
- External links
Abstract
One of the most significant challenges for today's interactive visualization is the efficient analysis and visualization of large-scale data, and I/O becomes a significant performance bottleneck. This thesis proposes a new data management policy to support interactive large-scale visual analytics. Our method can characterize user's data access patterns according to their data-dependent and view-dependent visualization operations, and leverage application knowledge to derive a novel scheme to predict data access during the interactive operations. Based on the prediction results, we develop a data replacement policy to exploit data locality and minimize data movement across multiple levels of a memory hierarchy. We evaluated our approach on machines with multiple hierarchical memory levels and compared it with state-of-the-art data replacement methods to demonstrate the effectiveness of our approach. Adviser: Hongfeng Yu.
