大规模非结构网格上基于PC的流线可视化研究

针对大规模非结构网格,提出了两种基于PC的流线可视化方法：内存映像文件方法（MMFM）和多线程out-of-core方法（MTOM）。利用八叉树空间划分大规模非结构网格,并讨论了数据块的组织结构。MMFM将大规模数据文件映像成虚拟RAM,流线构造与in-core方法类似,利用空间分块组织数据,减少缺页请求。MTOM利用多线程技术实现out-of-core流线构造,使得CPU和I／O重叠,隐藏时延,在多CPU上还可并行处理。测试结果表明,MMFM,MTOM都可利用较少内存进行大规模非结构网格的流线可视化,取得了较好的性能。     

Optimization and Performance of a Fortran 90 MPI-Based Unstructured Code on Large-Scale Parallel Systems

The message-passing interface (MPI) has become the standard in achieving effective results when using the message passing paradigm of parallelization. Codes written using MPI are extremely portable and are applicable to both clusters and massively parallel computing platforms. Since MPI uses the single program, multiple data (SPMD) approach to parallelism, good performance requires careful tuning of the serial code as well as careful data and control flow analysis to limit communication. We discuss optimization strategies used and their degree of success to increase performance of an MPI-based unstructured finite element simulation code written in Fortran 90. We discuss performance results based on implementations using several modern massively parallel computing platforms including the SGI Origin 3800, IBM Nighthawk 2 SMP, and Cray T3E-1200.     

非结构网格并行计算预处理方法研究

非结构网格预处理方法是非结构网格CFD并行计算的关键技术之一。提出基于缓冲数据结构的快速搜索算法来建立全局网格单元邻接关系图,算法复杂度低,能够显著降低非结构网格预处理的存储需求;在提高核心计算访存命中率方面,提出网格单元重排序算法,该算法能够提高核心计算效率,并通用于各种非结构网格问题。实验结果表明,在用于大网格量的复杂计算区域时该非结构网格预处理技术仍能得到较理想的结果。     

Analysis and shape optimization in incompressible flows with unstructured grids

The aim of this study is to develop and validate numerical methods that perform shape optimization in incompressible flows using unstructured meshes. The three-dimensional Euler equations for compressible flow are modified using the idea of artificial compressibility and discretized on unstructured tetrahedral grids to provide estimates of pressure distributions for aerodynamic configurations. Convergence acceleration techniques like multigrid and residual averaging are used along with parallel computing platforms to enable these simulations to be performed in a few minutes. This computational frame-work is used to analyze sail geometries. The adjoint equations corresponding to the “incompressible” field equations are derived along with the functional form of gradients. The evaluation of the gradients is reduced to an integral around the boundary to circumvent hurdles posed by adjoint-based gradient evaluations on unstructured meshes. The reduced gradient evaluations provide major computational savings for unstructured grids and its accuracy and use for canonical and industrial problems is a major contribution of this study. The design process is driven by a steepest-descent algorithm with a fixed step-size. The feasibility of the design process is demonstrated for three inverse design problems, two canonical problems and one industrial problem.     

Conservation properties of a new unstructured staggered scheme

In Wenneker et al. [Computation of compressible flows on unstructured staggered grids. In: Oñate E, Bugeda G, Suárez B, editors. Proceedings European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2000, Barcelona, 11-14 September 2000, Barcelona, 2000. CIMNE. http://ta.twi.tudelft.nl/users/wesseling/pub.html] an unstructured staggered scheme for the two-dimensional (2D) Euler equations is discussed. Such a scheme cannot be in classic conservation form for momentum. The aim of the present paper is to formulate a generalized conservation form for momentum on unstructured staggered grids, and to demonstrate by numerical experiments that the scheme satisfies the Rankine-Hugoniot conditions. Numerical results for 1D Riemann problems on 2D unstructured grids confirm that the scheme converges to the entropy solution. In addition, transonic flow around an airfoil is computed.     

基于GPU的非结构化网格数据体光照计算与实现方法

光照在提高体绘制质量方面发挥重要作用,而梯度计算是实现体光照的关键.与结构化网格相比,非结构化网格拓扑关系复杂,使得顶点梯度估计困难,采样点梯度计算复杂度高,且不易采用GPU加速,阻碍了算法的实时性.因此,绝大多数非结构化网格体绘制尚未添加体光照.本文提出一种高精度的非结构化网格顶点梯度计算方法:先采用格林公式估计单元...     

A Procedure for Tetrahedral Boundary Layer Mesh Generation

. We develop a methodology for introducing regions of high anisotropy in existing isotropic unstructured grids in complex, curved, three-dimensional domains. The new procedures are here applied to the capturing of solution features in the proximity of model boundaries (e.g. boundary layers). Suitable voids are created in an existing grid in the regions of localization using a mesh motion algorithm that solves a fictitious elasticity problem. The voids are then filled with stacks of prisms that are subsequently tetrahedronized to yield a simplicial mesh. The mesh motion algorithm allows us to deal in a simple and effective manner with the problem of self-intersection of elements in concave regions of the model boundaries, and in the case of closely spaced model faces, avoiding the need for cross-over checks and complex grid correction procedures. The capabilities and performance of the proposed methodology are illustrated with the help of practical examples.     

基于Haar纹理的非结构化道路消失点检测

由于非结构化道路缺乏明显的车道标识线或车道边界,使得其检测面临很大困难.利用非结构化道路的消失点作为约束,可以显著提高非结构化道路的检测性能.但基于多尺度多方向Gabor纹理的消失点检测方法存在计算量较大的问题,并且背景干扰也常会使得现有的消失点投票方法出现大的误检.为此提出一种基于类Haar特征的非结构化道路纹理快速提取方法,该方法利用设计的实部及虚部矩形模板,通过积分图技术实现了纹理特征的快速复响应;并在此基础上,提出利用正交校正及多样性投票方法,实现非结构化道路消失点的检测.在各种非结构化道路下比较了本文算法与现有两种最新的非结构化道路消失点检测算法,实验结果表明本文算法可以显著提高非结构化道路消失点的检测性能.     

A multi-faceted and automatic knowledge elicitation system (MAKES) for managing unstructured information

Management of unstructured information, such as emails, is vital for supporting knowledge work in professional services. However, the conventional way for managing unstructured information is inadequate as the knowledge work and associated tasks are becoming more complex, are dynamically changing with time and involve multiple concepts. This paper attempts to address the inadequacy, deficiency and limitations of the methods presently used to elicit knowledge from masses of unstructured information. These methods rely heavily on manpower, are time consuming and costly. With the development of a multi-faceted and automatic knowledge elicitation system (MAKES) manpower, time and cost can be dramatically reduced. The MAKES integrates the processes of collecting data, classifying unstructured information, modelling knowledge flow and social network analysis, and makes all of these actions into a connected process to audit unstructured information automatically. This audit is based on specific search criteria, search keywords, and the user behaviours of the knowledge workers. The unstructured information is automatically organized, classified and presented in a multi-facet taxonomy map. New concepts and knowledge are uncovered, analyzed and updated continuously from the incoming unstructured information, using a purpose-built knowledge elicitation algorithm named self-associated concept mapping (SACM). The capability and advantages of the MAKES are demonstrated through a successful trial implementation and a verification test conducted in an electronics trading company. Encouraging results have been achieved and a number of potential advantages have been realized. The area of application in this first deployment is based on an email-intensive organization and the proposed study will contribute to the advancement of methods and tools for managing other kinds of unstructured information.     

A General Performance Model of Structured and Unstructured Mesh Particle Transport Computations

The performance of unstructured mesh applications presents a number of complexities and subtleties that do not arise for dense structured meshes. From a programming point of view, the handling of unstructured meshes has an increased complexity in order to manage the necessary data structures and interactions between mesh-cells. From a performance point of view, there are added difficulties in understanding both the processing time on a single processor and the scaling characteristics when using large-scale parallel systems. In this work we present a general performance model for the calculation of deterministic S_N transport on unstructured meshes that is also applicable to structured meshes. The model captures the key processing characteristics of the calculation and is parametric using both system performance data (latency, bandwidth, processing rate etc.) and application data (mesh size etc.) as input. A single formulation of the model is used to predict the performance of two quite different implementations of the same calculation. It is validated on two clusters (an HP AlphaServer and an Itanium-2 system) showing high prediction accuracy.     

Spectral Difference Method for Unstructured Grids II: Extension to the Euler Equations

An efficient, high-order, conservative method named the spectral difference method has been developed recently for conservation laws on unstructured grids. It combines the best features of structured and unstructured grid methods to achieve high-computational efficiency and geometric flexibility; it utilizes the concept of discontinuous and high-order local representations to achieve conservation and high accuracy; and it is based on the finite-difference formulation for simplicity. The method is easy to implement since it does not involve surface or volume integrals. Universal reconstructions are obtained by distributing solution and flux points in a geometrically similar manner for simplex cells. In this paper, the method is further extended to nonlinear systems of conservation laws, the Euler equations. Accuracy studies are performed to numerically verify the order of accuracy. In order to capture both smooth feature and discontinuities, monotonicity limiters are implemented, and tested for several problems in one and two dimensions. The method is more efficient than the discontinuous Galerkin and spectral volume methods for unstructured grids.     

An improved multislope MUSCL scheme for solving shallow water equations on unstructured grids

This paper describes an improved vector manipulation multislope monotone upstream-centred scheme for conservation laws (MUSCL) reconstruction for solving the shallow water equations on unstructured grids. This improved MUSCL reconstruction method includes a bigger stencil for the interpolation and saves time for determining the geometric relations compared to the original vector manipulation method, so it is computationally more efficient and straightforward to implement. Four examples involving an analytical solution, laboratory experiments and field-scale measurements are used to test the performance of the proposed scheme. It has been proven that the proposed scheme can provide comparable accuracy and higher efficiency compared to the original vector manipulation method. With the increasing of the number of cells, the advantage of the proposed scheme becomes more apparent.     

Variational multiscale large-eddy simulations of the flow past a circular cylinder: Reynolds number effects

Variational multiscale large-eddy simulations (VMS–LES) of the flow around a circular cylinder are carried out at different Reynolds numbers in the subcritical regime, viz. Re = 3900, 10,000 and 20,000, based on the cylinder diameter. A mixed finite-element/finite-volume discretization on unstructured grids is used. The separation between the largest and the smallest resolved scales is obtained through a variational projection operator and finite-volume cell agglomeration. The WALE subgrid scale model is used to account for the effects of the unresolved scales; in the VMS approach, it is only added to the smallest resolved ones. The capability of this methodology to accurately predict the aerodynamic forces acting on the cylinder and in capturing the flow features are evaluated for the different Reynolds numbers considered. The sensitivity of the results to different simulation parameters, viz. agglomeration level and numerical viscosity, is also investigated at Re = 20,000.     

Image-consistent patches from unstructured points with J-linkage

Going from unstructured cloud of points to surfaces is a challenging problem. However, as points are produced by a structure-and-motion pipeline, image-consistency is a powerful clue that comes to the rescue. In this paper we present a method for extracting planar patches from an unstructured cloud of points, based on the detection of image-consistent planar patches with J-linkage, a robust algorithm for multiple model fitting. The method integrates several constraints inside J-linkage, optimizes the position of the points with regard to image-consistency and deploys a hierarchical processing scheme that decreases the computational load. With respect to previous work this approach has the advantage of starting from sparse data. Several results show the effectiveness of the proposed approach.     

Automated extraction of fragments of Bayesian networks from textual sources

Mining large amounts of unstructured data for extracting meaningful, accurate, and actionable information, is at the core of a variety of research disciplines including computer science, mathematical and statistical modelling, as well as knowledge engineering. In particular, the ability to model complex scenarios based on unstructured datasets is an important step towards an integrated and accurate knowledge extraction approach. This would provide a significant insight in any decision making process driven by Big Data analysis activities. However, there are multiple challenges that need to be fully addressed in order to achieve this, especially when large and unstructured data sets are considered.In this article we propose and analyse a novel method to extract and build fragments of Bayesian networks (BNs) from unstructured large data sources. The results of our analysis show the potential of our approach, and highlight its accuracy and efficiency. More specifically, when compared with existing approaches, our method addresses specific challenges posed by the automated extraction of BNs with extensive applications to unstructured and highly dynamic data sources.The aim of this work is to advance the current state-of-the-art approaches to the automated extraction of BNs from unstructured datasets, which provide a versatile and powerful modelling framework to facilitate knowledge discovery in complex decision scenarios.     

PostgreSQL与MongoDB处理非结构化数据性能比较

互联网技术的发展产生的海量非结构化数据在传统关系型数据库中难以被高速有效地进行存储和处理,各类NoSQL数据库可以有效存储处理非结构化数据,但是对关系运算功能的弱化难以满足应用场景的需求。具备非结构化数据处理能力的新型关系型数据库提供了适用多种应用场景的高效存储方式。为了能够定量地比较关系型数据库和面向文档的NoSQL数据库的数据存储与处理能力,比较了PostgreSQL的hstore数据类型和MongoDB的内嵌文档对非结构化数据的储存方式,并通过非结构化数据的批量加载、磁盘占用、主键查询、非主键查询、地理空间坐标查询等方面的对比来以分析性能特征与适用场景。     

Machine learning and BIM visualization for maintenance issue classification and enhanced data collection

Occupant-generated work orders are recognized as a good potential data to support Facility Management (FM) activities, however they are unstructured and rarely contain the specific information engineers require to resolve the reported issues. Instead, this often requires multiple trips are often needed to identify the required trade, identify the problem and required parts/tools, and resolve. A key challenge is data quality: free-form (unstructured) text is collected that frequently lacks necessary detail for problem diagnosis. Machine Learning provides new opportunities within the FM domain to improve the quality of information collected through online work order reporting systems by automatically classifying WOs and prompting building occupants with appropriate FM team-developed questions in real time to gather the required specific information in structured form. This paper presents the development, comparison, and application of two sets of supervised machine learning models to perform this classification for WOs generated from occupant complaints. A set of ∼150,000 historical WOs was used for model development and textual classification using with various term and itemset frequency approaches was tested. Classifier prediction accuracies ranged from 46.6% to 81.3% for classification by detailed subcategory; this increased to between 68% (simple term frequency) to 90% (random forest) when the dataset only included the ten most common (accounting for 70% of all WOs) subcategories. Hierarchical classification decreased performance. An FM-BIM integration approach is finally presented using the resultant classifiers to provide facilities management teams with spatio-temporal visualization of the work order categories across a series of buildings to help prioritize and streamline operations and maintenance task assignments.     

Modeling gossip-based content dissemination and search in distributed networking

This paper presents a rigorous analytic study of gossip-based message dissemination schemes that can be employed for content/service dissemination or discovery in unstructured and distributed networks. When using random gossiping, communication with multiple peers in one gossiping round is allowed. The algorithms studied in this paper are considered under different network conditions, depending on the knowledge of the state of the neighboring nodes in the network. Different node behaviors, with respect to their degree of cooperation and compliance with the gossiping process, are also incorporated. From the exact analysis, several important performance metrics and design parameters are analytically determined. Based on the proposed metrics and parameters, the performance of the gossip-based dissemination or search schemes, as well as the impact of the design parameters, are evaluated.     

Towards an efficient storage and retrieval mechanism for large unstructured grids

The size of spatial scientific datasets is steadily increasing due to improvements in instruments and availability of computational resources. However, much of the research on efficient storage and access to spatial datasets has focused on large multidimensional arrays. In contrast, unstructured grids consisting of collections of simplices (e.g. triangles or tetrahedra) present special challenges that have received less attention. Data values found at the vertices of the simplices may be dispersed throughout a datafile, producing especially poor disk locality.Our previous work has focused on addressing this locality problem. In this paper, we reorganize the unstructured grid to improve locality of disk access by maintaining the spatial neighborhood relationships inherent in the unstructured grid. This reorganization produces significant gains in performance by reducing the number of accesses made to the data file. We also examine the effects of different chunking configurations on data retrieval performance. A major motivation for reorganizing the unstructured grid is to allow the application of iteration aware prefetching. Applying this prefetching method to unstructured grids produces further performance gains over and above the gains seen from reorganization alone.The work presented in this journal contains at least 40% new material not included in our conference paper (Akande and Rhodes 2013).     

基于时空一致性的非结构化网格时变流场高效体绘制方法

时空一致性是时变流场的重要性质,也是加速时变数据可视化算法的关键.以硬件加速的光线投射算法(HRC)为框架,设计并实现了一种基于时空一致性的非结构化网格时变流场高效体绘制方法.首先提出一种分析非结构化网格单元和顶点数据时间一致性的方法,分别建立单元和顶点数据时间表,以降低绘制过程中的计算开销;然后设计一种单元和顶点数据相分离的GPU纹理结构,并采用一种小巧的单元梯度矩阵来降低显存开销;同时,设计了一种合理的数据调度策略,既能有效地避免绘制停顿,又使显存纹理结构更为紧致、高效.实验结果表明,该方法不仅明显地提高了绘制效率,而且具有更优显存空间利用率,能实现更大网格规模的非结构化网格时变流场数据体绘制.