Parallel algorithms for fractional and maximal independent sets in planar graphs
Discrete Applied Mathematics - Computational combinatiorics
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
View-dependent refinement of progressive meshes
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
A fast parallel algorithm for the maximal independent set problem
STOC '84 Proceedings of the sixteenth annual ACM symposium on Theory of computing
Photon mapping on programmable graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Parallel Triangular Mesh Decimation without Sorting
SCCG '01 Proceedings of the 17th Spring conference on Computer graphics
GPU-Based Tolerance Volumes for Mesh Processing
PG '04 Proceedings of the Computer Graphics and Applications, 12th Pacific Conference
GPUTeraSort: high performance graphics co-processor sorting for large database management
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Real-time mesh simplification using the GPU
Proceedings of the 2007 symposium on Interactive 3D graphics and games
GPU-Accelerated Shape Simplification for Mechanical-Based Applications
SMI '07 Proceedings of the IEEE International Conference on Shape Modeling and Applications 2007
AA-Sort: A New Parallel Sorting Algorithm for Multi-Core SIMD Processors
PACT '07 Proceedings of the 16th International Conference on Parallel Architecture and Compilation Techniques
Sorting networks and their applications
AFIPS '68 (Spring) Proceedings of the April 30--May 2, 1968, spring joint computer conference
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Preparing a CAD model for Finite Element (FE) analysis can be a time-consuming task, where shape and mesh simplifications play an important role. It is important that the simplified model has the same mechanical properties as the original one, and that the deviation from the original stays within a given tolerance. Most FE mesh simplification algorithms are either fully or partially sequential, and are therefore not suitable for architectures with high levels of parallelism. Furthermore, the use of processors such as GPUs of IBMs Cell BE require algorithms to be adapted to benefit from their computational advantages. Here, we present an algorithm written for parallel processors, and its implementation for the Cell BE.