Effective Large Scale Computing Software for Parallel Mesh Generation

Scientists commonly turn to supercomputers or Clusters of Workstations with hundreds (even thousands) of nodes to generate meshes for large-scale simulations. Parallel mesh generation software is then used to decompose the original mesh generation problem into smaller sub-problems that can be solved (meshed) in parallel. The size of the final mesh is limited by the amount of aggregate memory of the parallel machine. Also, requesting many compute nodes on a shared computing resource may result in a long waiting, far surpassing the time it takes to solve the problem.;These two problems (i.e., insufficient memory when computing on a small number of nodes, and long waiting times when using many nodes from a shared computing resource) can be addressed by using out-of-core algorithms. These are algorithms that keep most of the dataset out-of-core (i.e., outside of memory, on disk) and load only a portion in-core (i.e., into memory) at a time.;We explored two approaches to out-of-core computing. First, we presented a traditional approach, which is to modify the existing in-core algorithms to enable out-of-core computing. While we achieved good performance with this approach the task is complex and labor intensive. An alternative approach, we presented a runtime system designed to support out-of-core applications. It requires little modification of the existing in-core application code and still produces acceptable results. Evaluation of the runtime system showed little performance degradation while simplifying and shortening the development cycle of out-of-core applications. The overhead from using the runtime system for small problem sizes is between 12% and 41% while the overlap of computation, communication and disk I/O is above 50% and as high as 61% for large problems.;The main contribution of our work is the ability to utilize computing resources more effectively. The user has a choice of either solving larger problems, that otherwise would not be possible, or solving problems of the same size but using fewer computing nodes, thus reducing the waiting time on shared clusters and supercomputers. We demonstrated that the latter could potentially lead to substantially shorter wall-clock time

Enabling technology for non-rigid registration during image-guided neurosurgery

In the context of image processing, non-rigid registration is an operation that attempts to align two or more images using spatially varying transformations. Non-rigid registration finds application in medical image processing to account for the deformations in the soft tissues of the imaged organs. During image-guided neurosurgery, non-rigid registration has the potential to assist in locating critical brain structures and improve identification of the tumor boundary. Robust non-rigid registration methods combine estimation of tissue displacement based on image intensities with the spatial regularization using biomechanical models of brain deformation. In practice, the use of such registration methods during neurosurgery is complicated by a number of issues: construction of the biomechanical model used in the registration from the image data, high computational demands of the application, and difficulties in assessing the registration results. In this dissertation we develop methods and tools that address some of these challenges, and provide components essential for the intra-operative application of a previously validated physics-based non-rigid registration method.;First, we study the problem of image-to-mesh conversion, which is required for constructing biomechanical model of the brain used during registration. We develop and analyze a number of methods suitable for solving this problem, and evaluate them using application-specific quantitative metrics. Second, we develop a high-performance implementation of the non-rigid registration algorithm and study the use of geographically distributed Grid resources for speculative registration computations. Using the high-performance implementation running on the remote computing resources we are able to deliver the results of registration within the time constraints of the neurosurgery. Finally, we present a method that estimates local alignment error between the two images of the same subject. We assess the utility of this method using multiple sources of ground truth to evaluate its potential to support speculative computations of non-rigid registration

Polylidar3D -- Fast Polygon Extraction from 3D Data

Flat surfaces captured by 3D point clouds are often used for localization, mapping, and modeling. Dense point cloud processing has high computation and memory costs making low-dimensional representations of flat surfaces such as polygons desirable. We present Polylidar3D, a non-convex polygon extraction algorithm which takes as input unorganized 3D point clouds (e.g., LiDAR data), organized point clouds (e.g., range images), or user-provided meshes. Non-convex polygons represent flat surfaces in an environment with interior cutouts representing obstacles or holes. The Polylidar3D front-end transforms input data into a half-edge triangular mesh. This representation provides a common level of input data abstraction for subsequent back-end processing. The Polylidar3D back-end is composed of four core algorithms: mesh smoothing, dominant plane normal estimation, planar segment extraction, and finally polygon extraction. Polylidar3D is shown to be quite fast, making use of CPU multi-threading and GPU acceleration when available. We demonstrate Polylidar3D's versatility and speed with real-world datasets including aerial LiDAR point clouds for rooftop mapping, autonomous driving LiDAR point clouds for road surface detection, and RGBD cameras for indoor floor/wall detection. We also evaluate Polylidar3D on a challenging planar segmentation benchmark dataset. Results consistently show excellent speed and accuracy.Comment: 40 page

NASA high performance computing and communications program

The National Aeronautics and Space Administration's HPCC program is part of a new Presidential initiative aimed at producing a 1000-fold increase in supercomputing speed and a 100-fold improvement in available communications capability by 1997. As more advanced technologies are developed under the HPCC program, they will be used to solve NASA's 'Grand Challenge' problems, which include improving the design and simulation of advanced aerospace vehicles, allowing people at remote locations to communicate more effectively and share information, increasing scientist's abilities to model the Earth's climate and forecast global environmental trends, and improving the development of advanced spacecraft. NASA's HPCC program is organized into three projects which are unique to the agency's mission: the Computational Aerosciences (CAS) project, the Earth and Space Sciences (ESS) project, and the Remote Exploration and Experimentation (REE) project. An additional project, the Basic Research and Human Resources (BRHR) project exists to promote long term research in computer science and engineering and to increase the pool of trained personnel in a variety of scientific disciplines. This document presents an overview of the objectives and organization of these projects as well as summaries of individual research and development programs within each project

Galois : a system for parallel execution of irregular algorithms

textA programming model which allows users to program with high productivity and which produces high performance executions has been a goal for decades. This dissertation makes progress towards this elusive goal by describing the design and implementation of the Galois system, a parallel programming model for shared-memory, multicore machines. Central to the design is the idea that scheduling of a program can be decoupled from the core computational operator and data structures. However, efficient programs often require application-specific scheduling to achieve best performance. To bridge this gap, an extensible and abstract scheduling policy language is proposed, which allows programmers to focus on selecting high-level scheduling policies while delegating the tedious task of implementing the policy to a scheduler synthesizer and runtime system. Implementations of deterministic and prioritized scheduling also are described. An evaluation of a well-studied benchmark suite reveals that factoring programs into operators, schedulers and data structures can produce significant performance improvements over unfactored approaches. Comparison of the Galois system with existing programming models for graph analytics shows significant performance improvements, often orders of magnitude more, due to (1) better support for the restrictive programming models of existing systems and (2) better support for more sophisticated algorithms and scheduling, which cannot be expressed in other systems.Computer Science

Efficient integration of software components for scientific simulations

Abstract unavailable please refer to PD

Proceedings, MSVSCC 2015

The Virginia Modeling, Analysis and Simulation Center (VMASC) of Old Dominion University hosted the 2015 Modeling, Simulation, & Visualization Student capstone Conference on April 16th. The Capstone Conference features students in Modeling and Simulation, undergraduates and graduate degree programs, and fields from many colleges and/or universities. Students present their research to an audience of fellow students, faculty, judges, and other distinguished guests. For the students, these presentations afford them the opportunity to impart their innovative research to members of the M&S community from academic, industry, and government backgrounds. Also participating in the conference are faculty and judges who have volunteered their time to impart direct support to their students’ research, facilitate the various conference tracks, serve as judges for each of the tracks, and provide overall assistance to this conference. 2015 marks the ninth year of the VMASC Capstone Conference for Modeling, Simulation and Visualization. This year our conference attracted a number of fine student written papers and presentations, resulting in a total of 51 research works that were presented. This year’s conference had record attendance thanks to the support from the various different departments at Old Dominion University, other local Universities, and the United States Military Academy, at West Point. We greatly appreciated all of the work and energy that has gone into this year’s conference, it truly was a highly collaborative effort that has resulted in a very successful symposium for the M&S community and all of those involved. Below you will find a brief summary of the best papers and best presentations with some simple statistics of the overall conference contribution. Followed by that is a table of contents that breaks down by conference track category with a copy of each included body of work. Thank you again for your time and your contribution as this conference is designed to continuously evolve and adapt to better suit the authors and M&S supporters. Dr.Yuzhong Shen Graduate Program Director, MSVE Capstone Conference Chair John ShullGraduate Student, MSVE Capstone Conference Student Chai

ICASE/LaRC Workshop on Adaptive Grid Methods

Solution-adaptive grid techniques are essential to the attainment of practical, user friendly, computational fluid dynamics (CFD) applications. In this three-day workshop, experts gathered together to describe state-of-the-art methods in solution-adaptive grid refinement, analysis, and implementation; to assess the current practice; and to discuss future needs and directions for research. This was accomplished through a series of invited and contributed papers. The workshop focused on a set of two-dimensional test cases designed by the organizers to aid in assessing the current state of development of adaptive grid technology. In addition, a panel of experts from universities, industry, and government research laboratories discussed their views of needs and future directions in this field

Malhas adaptativas aplicadas em simulação numérica de manto de gelo marinho

Orientador: Philippe Remy Bernard DevlooTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Civil, Arquitetura e UrbanismoResumo: Projeções acuradas da evolução de mantos de gelo marinho e suas contribuições ao aumento do nível dos mares sob mudanças climáticas requerem alta resolução de malha/grade em modelos numéricos para capturar corretamente processos físicos fundamentais, tais como a evolução da linha de aterramento, a região onde o gelo apoiado sobre o embasamento rochoso começa a flutuar. A evolução da linha de aterramento desempenha um papel importante na dinâmica dos mantos de gelo marinho, já que exerce um controle fundamental sobre a estabilidade do manto de gelo apoiado. A modelagem numérica da dinâmica da linha de aterramento requer recursos computacionais significativos, pois a exatidão de sua posição depende da resolução da malha ou grade. Uma técnica numérica que contribui para a exatidão com custo computacional reduzido é o refinamento adaptativo de malhas. Apresentamos aqui a implementação de malhas adaptativas no Ice Sheet System Model para simular a dinâmica da linha de aterramento sob dois diferentes benchmarks: MISMIP3d e MISMIP+. Testamos diferentes critérios de refinamento baseados em: (a) distância ao redor da linha de aterramento, (b) estimador de erro a posteriori, o estimador de erro Zienkiewicz-Zhu e (c) diferentes combinações de (a) e (b). Em ambos benchmarks, os estimadores de erro apresentam valores altos em torno da linha de aterramento. Particularmente para o MISMIP+, o estimador também apresenta valores altos na parte apoiada do manto de gelo, seguindo as principais feições da geometria do leito rochoso. O emprego do estimator de erro orienta o procedimento de refinamento de forma que o desempenho das malhas adaptativas é otimizado. Nossos resultados mostram que o tempo computacional utilizando malhas adaptativas depende da acurácia requerida, mas em todos os casos, é significativamente menor em comparação com o tempo necessário ao empregar malhas uniformemente refinadas. Concluímos que o emprego de malhas adaptativas em simulação numérica de mantos de gelo marinho sem um estimador de erro associado deve ser evitado, especialmente em mantos de gelo reais em que o leito rochoso apresenta feições mais complexasAbstract: Accurate projections of the evolution of marine ice sheets and their contribution to sea level rise in a changing climate require a fine mesh/grid resolution in ice sheet models to correctly capture fundamental physical processes, such as the evolution of the grounding line, the region where grounded ice starts to float. The evolution of the grounding line indeed plays a major role in marine ice sheet dynamics, as it is a fundamental control on marine ice sheet stability. Numerical modeling of a grounding line requires significant computational resources since the accuracy of its position depends on grid or mesh resolution. A technique that improves accuracy with reduced computational cost is the adaptive mesh refinement approach. We present here the implementation of the adaptive mesh refinement technique in the parallel finite element Ice Sheet System Model to simulate grounding line dynamics under two different under two different benchmarks: MISMIP3d and MISMIP+. We test different refinement criteria: (a) distance around the grounding line, (b) a posteriori error estimator, the Zienkiewicz¿Zhu error estimator, and (c) different combinations of (a) and (b). In both benchmarks, the error estimator presents high values around the grounding line. In the MISMIP+ setup, this estimator also presents high values in the grounded part of the ice sheet, following the complex shape of the bedrock geometry. The error estimator helps guide the refinement procedure such that the mesh adaptivity performance is improved. Our results show that computational time with adaptive mesh depends on the required accuracy, but in all cases, it is significantly shorter than for uniformly refined meshes. We conclude that the use of adaptive mesh refinement in marine ice sheet simulations without an associated error estimator should be avoided, especially for real glaciers that have a complex bed geometryDoutoradoEstruturas e GeotécnicaDoutor em Engenharia Civil140186/2015-8CNP