Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Designing a data structure for polyhedral surfaces
Proceedings of the fourteenth annual symposium on Computational geometry
A multi-threaded streaming pipeline architecture for large structured data sets
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
MPI-The Complete Reference, Volume 1: The MPI Core
MPI-The Complete Reference, Volume 1: The MPI Core
Circular incident edge lists: a data structure for rendering complex unstructured grids
Proceedings of the conference on Visualization '01
Large-Scale Data Visualization Using Parallel Data Streaming
IEEE Computer Graphics and Applications
A User''s Guide to CGNS
Hardware-Accelerated Reconstruction of Polygonal Isosurface Representations on Unstructured Grids
PG '04 Proceedings of the Computer Graphics and Applications, 12th Pacific Conference
KD-tree acceleration structures for a GPU raytracer
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Parallel Programming in C with MPI and OpenMP
Parallel Programming in C with MPI and OpenMP
Time Dependent Processing in a Parallel Pipeline Architecture
IEEE Transactions on Visualization and Computer Graphics
Real-time KD-tree construction on graphics hardware
ACM SIGGRAPH Asia 2008 papers
High performance multivariate visual data exploration for extremely large data
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
Intel threading building blocks
Intel threading building blocks
Query-Driven Visualization of Time-Varying Adaptive Mesh Refinement Data
IEEE Transactions on Visualization and Computer Graphics
Visualizing Temporal Patterns in Large Multivariate Data using Modified Globbing
IEEE Transactions on Visualization and Computer Graphics
A parallel algorithm for construction of uniform grids
Proceedings of the Conference on High Performance Graphics 2009
Distribution-Driven Visualization of Volume Data
IEEE Transactions on Visualization and Computer Graphics
Hybrid parallel programming with MPI and unified parallel C
Proceedings of the 7th ACM international conference on Computing frontiers
A Light-weight API for Portable Multicore Programming
PDP '10 Proceedings of the 2010 18th Euromicro Conference on Parallel, Distributed and Network-based Processing
Data-Parallel Octrees for Surface Reconstruction
IEEE Transactions on Visualization and Computer Graphics
A distributed data-parallel framework for analysis and visualization algorithm development
Proceedings of the 5th Annual Workshop on General Purpose Processing with Graphics Processing Units
VISSYM'04 Proceedings of the Sixth Joint Eurographics - IEEE TCVG conference on Visualization
SCC '12 Proceedings of the 2012 SC Companion: High Performance Computing, Networking Storage and Analysis
A Survey of Visualization Pipelines
IEEE Transactions on Visualization and Computer Graphics
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As the number of cores in processors increase and accelerator architectures are becoming more common, an ever greater number of threads is required to achieve full processor utilization. Our current parallel scientific visualization codes rely on partitioning data to achieve parallel processing, but this approach will not scale as we approach massive threading in which work is distributed in such a fine level that each thread is responsible for a minute portion of data. In this paper we characterize the challenges of refactoring our current visualization algorithms by considering the finest portion of work each performs and examining the domain of input data, overlaps of output domains, and interdependencies among work instances. We divide our visualization algorithms into eight categories, each containing algorithms with the same interdependencies. By focusing our research efforts to solving these categorial challenges rather than this legion of individual algorithms, we can make attainable advancement for extreme computing.