Abstract
A key component of most large-scale rendering systems is a parallel image compositing algorithm, and the most commonly used compositing algorithms are binary swap and its variants. Although shown to be very efficient, one of the classic limitations of binary swap is that it only works on a number of processes that is a perfect power of 2. Multiple variations of binary swap have been independently introduced to overcome this limitation and handle process counts that have factors that are not 2. To date, few of these approaches have been directly compared against each other, making it unclear which approach is best. This paper presents a fresh implementation of each of these methods using a common software framework to make them directly comparable. These methods to run binary swap with odd factors are directly compared. The results show that some simple compositing approaches work as well or better than more complex algorithms that are more difficult to implement.
Original language | English |
---|---|
Title of host publication | 2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 56-60 |
Number of pages | 5 |
ISBN (Electronic) | 9781538668733 |
DOIs | |
State | Published - Oct 2018 |
Externally published | Yes |
Event | 8th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2018 - Berlin, Germany Duration: Oct 21 2018 → … |
Publication series
Name | 2018 IEEE 8th Symposium on Large Data Analysis and Visualization, LDAV 2018 |
---|
Conference
Conference | 8th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2018 |
---|---|
Country/Territory | Germany |
City | Berlin |
Period | 10/21/18 → … |
Funding
This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, under Award Number 14-017566. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND 2018-9004 C
Keywords
- Computer graphics
- computing methodologies
- massively parallel algorithms
- parallel algorithms
- parallel computing methodologies
- rendering; Computing methodologies