A data distributed, parallel algorithm for ray-traced volume rendering
PRS '93 Proceedings of the 1993 symposium on Parallel rendering
Parallel volume-rendering algorithm performance on mesh-connected multicomputers
PRS '93 Proceedings of the 1993 symposium on Parallel rendering
A Sorting Classification of Parallel Rendering
IEEE Computer Graphics and Applications
Communication Costs for Parallel Volume-Rendering Algorithms
IEEE Computer Graphics and Applications
Hybrid sort-first and sort-last parallel rendering with a cluster of PCs
HWWS '00 Proceedings of the ACM SIGGRAPH/EUROGRAPHICS workshop on Graphics hardware
Parallel rendering with k-way replication
PVG '01 Proceedings of the IEEE 2001 symposium on parallel and large-data visualization and graphics
Sort-last parallel rendering for viewing extremely large data sets on tile displays
PVG '01 Proceedings of the IEEE 2001 symposium on parallel and large-data visualization and graphics
Parallel Volume Rendering Using Binary-Swap Compositing
IEEE Computer Graphics and Applications
Scalable Rendering on PC Clusters
IEEE Computer Graphics and Applications
ICPP '99 Proceedings of the 1999 International Conference on Parallel Processing
An improvement on binary-swap compositing for sort-last parallel rendering
Proceedings of the 2003 ACM symposium on Applied computing
SLIC: Scheduled Linear Image Compositing for Parallel Volume Rendering
PVG '03 Proceedings of the 2003 IEEE Symposium on Parallel and Large-Data Visualization and Graphics
From mesh generation to scientific visualization: an end-to-end approach to parallel supercomputing
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Planning Algorithms
An efficient format for nearly constant-time access to arbitrary time intervals in large trace files
Scientific Programming - Large-Scale Programming Tools and Environments
Massively parallel volume rendering using 2-3 swap image compositing
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
A configurable algorithm for parallel image-compositing applications
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
In Situ Visualization at Extreme Scale: Challenges and Opportunities
IEEE Computer Graphics and Applications
End-to-End Study of Parallel Volume Rendering on the IBM Blue Gene/P
ICPP '09 Proceedings of the 2009 International Conference on Parallel Processing
Extreme Scaling of Production Visualization Software on Diverse Architectures
IEEE Computer Graphics and Applications
In Situ Visualization for Large-Scale Combustion Simulations
IEEE Computer Graphics and Applications
Remote large data visualization in the paraview framework
EG PGV'06 Proceedings of the 6th Eurographics conference on Parallel Graphics and Visualization
MPI-hybrid parallelism for volume rendering on large, multi-core systems
EG PGV'10 Proceedings of the 10th Eurographics conference on Parallel Graphics and Visualization
Accelerating and benchmarking radix-k image compositing at large scale
EG PGV'10 Proceedings of the 10th Eurographics conference on Parallel Graphics and Visualization
Revisiting parallel rendering for shared memory machines
EG PGV'11 Proceedings of the 11th Eurographics conference on Parallel Graphics and Visualization
Versatile communication algorithms for data analysis
EuroMPI'12 Proceedings of the 19th European conference on Recent Advances in the Message Passing Interface
NUMA-aware image compositing on multi-GPU platform
The Visual Computer: International Journal of Computer Graphics
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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. The fundamental operation of sort-last parallel rendering is an image composite, 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 image compositing algorithms has been with an arbitrary set of enhancements, if any are applied at all. In this paper we take a leading production-quality image-compositing framework, IceT, and use 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 Blue-Gene/P at Argonne National Laboratories.