SCHEDULE: NOV 12-18, 2011

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An Image Compositing Solution at Scale

SESSION: Applications

EVENT TYPE: Paper

TIME: 4:30PM - 5:00PM

AUTHOR(S):Kenneth Moreland, Wesley Kendall, Tom Peterka, Jian Huang

ROOM:TCC 304

ABSTRACT:
The only proven method for performing distributed-memory parallel rendering at large scales, tens of thousands of nodes, is a class of algorithms called sort last, which combines a collection of images generated independently on each node into a single blended image. Over the years numerous image compositing algorithms have been proposed as well as several enhancements and rendering modes to these core algorithms. However, the testing of these algorithms has been with arbitrary, if any, enhancements. This paper takes a leading production-quality image-compositing framework, IceT, and uses it as a testing framework for the leading image compositing algorithms of today. As we scale IceT to ever increasing job sizes, we consider the image compositing systems holistically, incorporate numerous optimizations, and discover several improvements to the process never considered before. We conclude by demonstrating our solution on 64K cores of the Intrepid BlueGene/P at Argonne National Laboratories.

Chair/Author Details:

Kenneth Moreland - Sandia National Laboratories

Wesley Kendall - University of Tennessee, Knoxville

Tom Peterka - Argonne National Laboratory

Jian Huang - University of Tennessee, Knoxville

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The full paper can be found in the ACM Digital Library