Student Contribution

SC Conference - Activity Details

Massively Parallel Volume Rendering Using 2-3 Swap Image Compositing

Hongfeng Yu  (University of California, Davis)
Chaoli Wang  (University of California, Davis)
Kwan-Liu Ma  (University of California, Davis)
Papers Session
Visualization and Data Management
Thursday,  02:00PM - 02:30PM
Room Ballroom G
The ever-increasing amounts of simulation data produced by scientists demand high-end parallel visualization capability. However, image compositing, which requires inter-processor communication, is often the bottleneck stage for parallel rendering of large volume data sets. Existing image compositing solutions either incur a large number of messages exchanged among processors (such as the direct send method), or limit the number of processors that can be effectively utilized (such as the binary swap method). We introduce a new image compositing algorithm, called 2-3 swap, which combines the flexibility of the direct send method and the optimality of the binary swap method. Our 2-3 swap algorithm allows an arbitrary number of processors to be used for compositing, and fully utilizes all participating processors throughout the course of the compositing. We experiment with our image compositing solution on a supercomputer with thousands of processors, and demonstrate its great flexibility as well as scalability.
The full paper can be found in the IEEE Xplore Digital Library and ACM Digital Library
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