Towards Exascale Parallel Delaunay Mesh Generation

Chrisochoides, Nikos; Chernikov, Andrey N.; Fedorov, Andriy; Kot, Andriy; Linardakis, Leonidas; Foteinos, Panagiotis A.

doi:10.1007/978-3-642-04319-2_19

Cited by 21 publications

(18 citation statements)

References 35 publications

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“…It seems that after 144 cores, this pressure on the switches slows performance down. A hybrid approach [22] able to scale for larger network hierarchies is left for future work. The 368,974 element mesh generated by PI2M with input image the MRI knee atlas [48].…”

Section: Weak Scaling Resultsmentioning

confidence: 99%

“…In the future, we plan to increase scalability by employing a hierarchically layered (distributed and shared memory) implementation design [22] and combine this tightly-coupled method with the decoupled and partially coupled methods we developed in the past, exploring in this way different levels of concurrency.…”

Section: Discussion Conclusion and Future Workmentioning

confidence: 97%

“…We show that this deterioration is not because of load imbalance or high thread contention, but because of the intensive and hop-wise slower communication traffic involved in increased problem sizes. This problem could be potentially be alleviated by using hybrid approaches to explore network hierarchies [22]. However, this is outside the scope of the paper.…”

Section: Introductionmentioning

confidence: 98%

“…Our goal is to develop the most efficient and scalable method on a moderate number of cores. Our long term goal is to increase scalability by exploiting concurrency at different levels [22].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

High quality real-time image-to-mesh conversion for finite element simulations

Foteinos

Chrisochoides

2013

Proceedings of the 27th International ACM Conference on International Conference on Supercomputing

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In this paper, we present a parallel Image-to-Mesh Conversion (I2M) algorithm with quality and fidelity guarantees achieved by dynamic point insertions and removals. Starting directly from an image, it is able to recover the isosurface and mesh the volume with tetrahedra of good shape. Our tightly-coupled shared-memory parallel speculative execution paradigm employs carefully designed contention managers, load balancing, synchronization and optimizations schemes which boost the parallel efficiency with little overhead: our single-threaded performance is faster than CGAL, the state of the art sequential mesh generation software we are aware of. The effectiveness of our method is shown on Blacklight, the Pittsburgh Supercomputing Center's cache-coherent NUMA machine, via a series of case studies justifying our choices. We observe a more than 82% strong scaling efficiency for up to 64 cores, and a more than 95% weak scaling efficiency for up to 144 cores, reaching a rate of 14.7 Million Elements per second. To the best of our knowledge, this is the fastest and most scalable 3D Delaunay refinement algorithm.

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Section: Weak Scaling Resultsmentioning

confidence: 99%

Section: Discussion Conclusion and Future Workmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

High quality real-time image-to-mesh conversion for finite element simulations

Foteinos

Chrisochoides

2013

Proceedings of the 27th International ACM Conference on International Conference on Supercomputing

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“…Heuristics can be used to anticipate the new size of the partitions as the grid is modified, but the change in partition size introduces more complexity than the typically static stencil and communication pattern of the CFD solver. Chrisochoides et al 63,64 proposes that a hierarchical parallel execution scheme will be required on the architectures anticipated by the CFD Vision 2030 Study.…”

Section: 54mentioning

confidence: 99%

Unstructured Grid Adaptation: Status, Potential Impacts, and Recommended Investments Towards CFD 2030

Park

Krakos

Michal

et al. 2016

46th AIAA Fluid Dynamics Conference

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Unstructured grid adaptation is a powerful tool to control Computational Fluid Dynamics (CFD) discretization error. It has enabled key increases in the accuracy, automation, and capacity of some fluid simulation applications. Slotnick et al. provide a number of case studies in the CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences to illustrate the current state of CFD capability and capacity. The study authors forecast the potential impact of emerging High Performance Computing (HPC) environments forecast in the year 2030 and identify that mesh generation and adaptivity will continue to be significant bottlenecks in the CFD workflow. These bottlenecks may persist because very little government investment has been targeted in these areas. To motivate investment, the impacts of improved grid adaptation technologies are identified. The CFD Vision 2030 Study roadmap and anticipated capabilities in complementary disciplines are quoted to provide context for the progress made in grid adaptation in the past fifteen years, current status, and a forecast for the next fifteen years with recommended investments. These investments are specific to mesh adaptation and impact other aspects of the CFD process. Finally, a strategy is identified to di↵use grid adaptation technology into production CFD work flows.

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A large‐scale parallel hybrid grid generation technique for realistic complex geometry

Zhao

Zhang

et al. 2020

Numerical Methods in Fluids

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Summary High‐Performance Computing (HPC) systems and Computational Fluid Dynamics (CFD) have made significant progress in recent years; however, as the basis of the large‐scale parallel computing, the massive grid generation of billions of cells has become a bottleneck problem. In this study, a parallel grid generation technique is proposed to generate large‐scale mixed grids with arbitrary cell types and scales. The basic idea of our method is analogous to the global mesh refinement technique. An initial coarse grid with arbitrary cell types is regarded as a background mesh which is partitioned into subzones, and subzones are assigned onto different CPU cores. After the cells and faces in each subzone are split, the inserted new points of the solid wall are projected onto the original CAD entities to preserve the geometry accurately. Finally, the tangled cells caused by the projection in the boundary layer are untangled by a local Radial Basis Function mesh deformation technique. Furthermore, a parallel partition approach and an efficient wall distance computing technique for massive grids are developed also to shorten the preprocessing time. The tests show that the preprocessing efficiency has been increased by two or three orders compared with traditional methods. Billions of grids are generated for the AIAA JSM high‐lift model and the Chinese CHN‐T1 transport model to test the ability of the parallel grid generation technique. The maximum scale up to 19 billion mixed elements is generated using 16 384 CPU cores in parallel, and the mesh quality is acceptable for CFD simulations.

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Towards Exascale Parallel Delaunay Mesh Generation

Cited by 21 publications

References 35 publications

High quality real-time image-to-mesh conversion for finite element simulations

High quality real-time image-to-mesh conversion for finite element simulations

Unstructured Grid Adaptation: Status, Potential Impacts, and Recommended Investments Towards CFD 2030

A large‐scale parallel hybrid grid generation technique for realistic complex geometry

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