5 citations · 8 across the 6 of their papers we have counts for
6 papers
Parallelizing Legacy Mesh Generation Software: Lessons Learned from a Pseudo-Constrained Parallel Data Refinement Approach for Advancing Front Local Reconnection
Kevin Garner, David Marcum, Nikos Chrisochoides
This paper presents lessons learned from parallelizing the legacy software known as Advancing Front Local Reconnection (AFLR) as a black box. The parallel procedure utilizes (i) a…
Distributed Semi-Speculative Parallel Anisotropic Mesh Adaptation
Kevin Garner, Polykarpos Thomadakis, Nikos Chrisochoides
This paper presents a distributed memory method for anisotropic mesh adaptation that is designed to avoid the use of collective communication and global synchronization techniques.…
3-Dimensional Adaptive Unstructured Tessellated Look-up Tables for the Approximation of Compton Form Factors
Charles Hyde, Mitch Kerver, Christos Tsolakis +8
We describe an iterative algorithm to construct an unstructured tessellation of simplices (irregular tetrahedra in 3-dimensions) to approximate an arbitrary function to a desired p…
Near Real-time Adaptive Isotropic and Anisotropic Image-to-mesh Conversion for Numerical Simulations Involving Cerebral Aneurysms
Kevin Garner, Fotis Drakopoulos, Chander Sadasivan +1
Presented are two techniques that are designed to help streamline the discretization of complex vascular geometries within the numerical modeling process. The first method integrat…
Image-To-Mesh Conversion for Biomedical Simulations
Fotis Drakopoulos, Kevin Garner, Christopher Rector +1
Converting a three-dimensional medical image into a 3D mesh that satisfies both the quality and fidelity constraints of predictive simulations and image-guided surgical procedures…
Towards Distributed Semi-speculative Adaptive Anisotropic Parallel Mesh Generation
Kevin Garner, Christos Tsolakis, Polykarpos Thomadakis +1
This paper presents the foundational elements of a distributed memory method for mesh generation that is designed to leverage concurrency offered by large-scale computing. To achie…