arXiv subjects

Kevin Garner

Publications and source records attributed to Kevin Garner.

6 recordsLinked to original sources

arXiv2026

Parallelizing Legacy Mesh Generation Software: Lessons Learned from a Pseudo-Constrained Parallel Data Refinement Approach for Advancing Front Local Reconnection

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 data decomposition scheme where each subdomain is refined in parallel using the sequential mesh generation code and (ii) a runtime system for work-load balancing. Results on the mesh refinement operation show that the parallel method's stability (output mesh quality) is good and that the parallel method outperforms the serial AFLR by about 11 times when utilizing 16 CPU cores. However, full stability (i.e., generating the same quality as the serial method) and potential scalability is limited due to the constraints set by the black box's input boundary requirement. Satisfying this requirement for each subdomain not only adds overhead but also causes the parallel method to generate a different output mesh volume than that generated by the serial method. The complexity of such a state-of-the-art code requires that it be modified to a non-trivial extent in order to remove these constraints. These results suggest that the parallelization of black-box legacy codes like AFLR may not be practical and instead encourages an approach that is originally designed without such constraints to efficiently leverage the concurrency offered by large-scale architectures.

cs.DC↗

arXiv2026

Distributed Semi-Speculative Parallel Anisotropic Mesh Adaptation

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. In the presented method, meshing functionality is separated from performance aspects by utilizing a separate entity for each - a multicore cc-NUMA-based (shared memory) mesh generation software and a parallel runtime system that is designed to help applications leverage the concurrency offered by emerging high-performance computing (HPC) architectures. First, an initial mesh is decomposed and its interface elements (subdomain boundaries) are adapted on a single multicore node (shared memory). Subdomains are then distributed among the nodes of an HPC cluster so that their interior elements are adapted while interface elements (already adapted) remain frozen to maintain mesh conformity. Lessons are presented regarding some re-designs of the shared memory software and how its speculative execution model is utilized by the distributed memory method to achieve good performance. The presented method is shown to generate meshes (of up to approximately 1 billion elements) with comparable quality and performance to existing state-of-the-art HPC meshing software.

cs.DC↗

arXiv2025

3-Dimensional Adaptive Unstructured Tessellated Look-up Tables for the Approximation of Compton Form Factors

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 precision by interpolation. The method is applied to the generation of Compton Form Factors for simulation and analysis of nuclear femtography, as enabled by high energy exclusive processes such as electron-proton scattering producing just an electron, proton, and gamma-ray in the final state. While producing tessellations with only a 1% mean interpolation error, our results show that the use of such tessellations can significantly decrease the computation time for Monte Carlo event generation by $\sim23$ times for $10^{7}$ events (and using extrapolation, by $\sim955$ times for $10^{10}$ events).

math.NA↗

arXiv2024

Near Real-time Adaptive Isotropic and Anisotropic Image-to-mesh Conversion for Numerical Simulations Involving Cerebral Aneurysms

Presented are two techniques that are designed to help streamline the discretization of complex vascular geometries within the numerical modeling process. The first method integrates multiple software tools into a single pipeline which can generate adaptive anisotropic meshes from segmented medical images. The pipeline is shown to satisfy quality, fidelity, smoothness, and robustness requirements while providing near real-time performance for medical image-to-mesh conversion. The second method approximates a user-defined sizing function to generate adaptive isotropic meshes of good quality and fidelity in real-time. Tested with two brain aneurysm cases and utilizing up to 96 CPU cores within a single, multicore node on Purdue University's Anvil supercomputer, the parallel adaptive anisotropic meshing method utilizes a hierarchical load balancing model (designed for large, cc-NUMA shared memory architectures) and contains an optimized local reconnection operation that performs three times faster than its original implementation from previous studies. The adaptive isotropic method is shown to generate a mesh of up to approximately 50 million elements in less than a minute while the adaptive anisotropic method is shown to generate approximately the same number of elements in about 5 minutes.

physics.flu-dyn↗

arXiv2024

Image-To-Mesh Conversion for Biomedical Simulations

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 remains a critical problem. Presented is an image-to-mesh conversion method called CBC3D. It first discretizes a segmented image by generating an adaptive Body-Centered Cubic (BCC) mesh of high-quality elements. Next, the tetrahedral mesh is converted into a mixed-element mesh of tetrahedra, pentahedra, and hexahedra to decrease element count while maintaining quality. Finally, the mesh surfaces are deformed to their corresponding physical image boundaries, improving the mesh's fidelity. The deformation scheme builds upon the ITK open-source library and is based on the concept of energy minimization, relying on a multi-material point-based registration. It uses non-connectivity patterns to implicitly control the number of extracted feature points needed for the registration and, thus, adjusts the trade-off between the achieved mesh fidelity and the deformation speed. We compare CBC3D with four widely used and state-of-the-art homegrown image-to-mesh conversion methods from industry and academia. Results indicate that the CBC3D meshes (i) achieve high fidelity, (ii) keep the element count reasonably low, and (iii) exhibit good element quality.

cs.GR↗

arXiv2023

Towards Distributed Semi-speculative Adaptive Anisotropic Parallel Mesh Generation

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 achieve this goal, meshing functionality is separated from performance aspects by utilizing a separate entity for each - a shared memory mesh generation code called CDT3D and PREMA for parallel runtime support. Although CDT3D is designed for scalability, lessons are presented regarding additional measures that were taken to enable the code's integration into the distributed memory method as a black box. In the presented method, an initial mesh is data decomposed and subdomains are distributed amongst the nodes of a high-performance computing (HPC) cluster. Meshing operations within CDT3D utilize a speculative execution model, enabling the strict adaptation of subdomains' interior elements. Interface elements undergo several iterations of shifting so that they are adapted when their data dependencies are resolved. PREMA aids in this endeavor by providing asynchronous message passing between encapsulations of data, work load balancing, and migration capabilities all within a globally addressable namespace. PREMA also assists in establishing data dependencies between subdomains, thus enabling "neighborhoods" of subdomains to work independently of each other in performing interface shifts and adaptation. Preliminary results show that the presented method is able to produce meshes of comparable quality to those generated by the original shared memory CDT3D code. Given the costly overhead of collective communication seen by existing state-of-the-art software, relative communication performance of the presented distributed memory method also shows that its emphasis on avoiding global synchronization presents a potentially viable solution in achieving scalability when targeting large configurations of cores.

cs.DC↗