改进的Potrace提花织物图像矢量化算法

为了对提花织物图像进行矢量化,针对其颜色少、色块大的特点,提出了改进的Potrace图像矢量化算法。原始的Potrace算法只能实现对二值图像的矢量化,改进后的算法将位图中的色块逐个分解生成一个个的闭合路径,之后将这些闭合路径按照其各自分布拼接成树状结构并矢量化,最终生成一个完整的矢量图形。该算法在实际的应用中取得较好效果。     

浅议一种彩色光栅图像矢量化的新方法

提出了合理运用图形处理软件对光栅底图进行去色、二值化、去斑点等处理,使其满足ArcGIS自动矢量化模块要求的新方法,指出该方法可以大大提高数字化工作的效率,减轻数字化工作的强度,以推广该彩色光栅图像矢量化方法的应用.     

通风机特性曲线图形矢量化技术

针对目前通风机特性曲线图形矢量化主要采用手工描点采集数据,使用Excel或自主开发软件绘图,数据采集和图形绘制是分离的,效率低且无法保证拟合曲线与原曲线的重合度等问题,利用矢量化方法,以原图为底板对曲线进行定位离散,并自动绘制出矢量图形。在此基础上,讨论了曲线采集点的数目和拟合方程的次数对拟合曲线重合度的影响。应用研究表明,该软件的效率是常规方法的5倍以上,自动绘制的图形与原图基本吻合,可以在现场推广应用。     

Optimization of finite element codes

A general algorithm for constructing finite element matrices within a multiple input, multiple data stream (MIMD) vector-processing environment is presented. Efficiency of the vectorized code is determined by the number of elements which differs from the more intuitive algorithms based on the number of quadrature points or shape functions. Performance is evaluated analytically and then verified by timings obtained by a series of experimental runs on a Cray Y-MP. A speedup factor of 25 is observed.     

反原形向量化与拟离散性

如何利用循环体诸如初值、终值、步长和下标式等数学对象的诸如恒等、正负、单调性一类的数学特征,按照严格推导出来的简单规则,绕过各种复杂的数据依赖关系图及其上诸如拓扑排序或等价变换等复杂的操作,直接从事向量化处理,这是极富实用价值的研究方向.文献[2,3,5]给出的可原形/准原形算法,以及本文的可反原形与拟离散性,正是这样的捷径.它们能使相当部分的常见循环,直接向量化.     

Vectorization and multitasking of dynamic programming in control: Experiments on a CRAY-2

Parallelism in dynamic programming is considered within the specificity of optimal control. We present the program PDVP developed for solving a general deterministic discrete-time optimization problem by means of a parallel dynamic programming algorithm on the state variables. Multitasking and vectorization are considered from the viewpoint to implement PDVP on a CRAY-2. The performances are analysed through a significant application to the optimization of satellite trajectories. Promising results are obtained.     

Evaluating vector data type usage in OpenCL kernels

Open Computing Language (OpenCL) is an open, functionally portable programming model for a large range of highly parallel processors. To provide users with access to the underlying platforms, OpenCL has explicit support for features such as local memory and vector data types (VDTs). However, these are often low‐level, hardware‐specific features, which can be detrimental to performance on different platforms. In this paper, we focus on VDTs and investigate their usage in a systematic way. First, we propose two different approaches (inter‐vdt and intra‐vdt) to use VDTs in OpenCL kernels, and show how to translate scalar OpenCL kernels to vectorized ones. After obtaining vectorized code, we evaluate the performance effects of using VDTs with two types of benchmarks: micro‐benchmarks and macro‐benchmarks. With micro‐benchmarks, we study the execution model of VDTs and the role of the compiler‐aided vectorizer on five devices. With macro‐benchmarks, we explore the changes of memory access patterns before and after using VDTs, and the resulting performance impact. Not only our evaluation provides insights into how OpenCL's VDTs are mapped on different processors, but it also indicates that using such data types introduces changes in both computation and memory accesses. Based on the lessons learned, we discuss how to deal with performance portability in the presence of VDTs. Copyright © 2014 John Wiley & Sons, Ltd.