Abstract
Scientific simulations typically store only a small fraction of computed timesteps due to storage and I/O bandwidth limitations. Previous work has demonstrated the compressibility of floating-point volume data, but such compression often comes with a tradeoff between computational complexity and the achievable compression ratio. This work demonstrates the use of special-purpose video encoding hardware on the GPU which is present but (to the best of our knowledge) completely unused in current GPU-equipped super computers such as Titan. We show that lossy encoding allows the output of far more data at sufficient quality for a posteriori rendering and analysis. We also show that the encoding can be computed in parallel to general-purpose computation due to the special-purpose hardware. Finally, we demonstrate such encoded volumes are inexpensive to decode in memory during analysis, making it unnecessary to ever store the decompressed volumes on disk.
Original language | English (US) |
---|---|
Title of host publication | 2017 IEEE 7th Symposium on Large Data Analysis and Visualization, LDAV 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 64-73 |
Number of pages | 10 |
Volume | 2017-December |
ISBN (Electronic) | 9781538606179 |
DOIs | |
State | Published - Dec 19 2017 |
Event | 7th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2017 - Phoenix, United States Duration: Oct 2 2017 → … |
Other
Other | 7th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2017 |
---|---|
Country | United States |
City | Phoenix |
Period | 10/2/17 → … |
Keywords
- Floating-point compression
- GPU video encoding
- Volume compression
ASJC Scopus subject areas
- Hardware and Architecture
- Information Systems
- Media Technology
- Library and Information Sciences