工程图纸中虚线的提取算法

本文提出了图纸转换系统中虚线提取的一个有效算法,算法由小短线的提取,种子短线的确认,小短线的吸收,粘连段的处理和段数的确定五个部分组成,本文详细介绍了这五个组成部分的实现过程,最后给出一个实例,结果证明该算法能有效处理图纸中大量存在的大部分虚线型。     

Performance evaluation of vector implementations of combinatorial algorithms

We study the performance and the use of vector computers for the solution of combinatorial optimization problems, particularly dynamic programming and shortest path problems. A general model for performance evaluation and vector implementations for the problems described above are studied. These implementations were done on a CRAY-1 vector computer and the computational results obtained show (i) the adequacy of the performance evaluation model and (ii) very important gains concerning computing times, showing that vector computers will be of great importance in the field of combinatorial optimization.     

Automatic Intra-Register Vectorization for the Intel® Architecture

Recent extensions to the Intel^® Architecture feature the SIMD technique to enhance the performance of computational intensive applications that perform the same operation on different elements in a data set. To date, much of the code that exploits these extensions has been hand-coded. The task of the programmer is substantially simplified, however, if a compiler does this exploitation automatically. The high-performance Intel^® C++/Fortran compiler supports automatic translation of serial loops into code that uses the SIMD extensions to the Intel^® Architecture. This paper provides a detailed overview of the automatic vectorization methods used by this compiler together with an experimental validation of their effectiveness.     

Parallel particle simulation in high voltage diodes (Algorithms and concepts for implementation on SUPRENUM)

A two-dimensional Particle-In-Cell (PIC) code has been developed in order to support the experimental investigation of pulsed power ion diodes by numerical simulation. The PIC code serves to simulate the orbits of electrically charged particles in electro-magnetic fields. Most modules of the PIC code have been vectorized; for parallelization the logical structure of the code is being considered. In this paper we introduce the idea of a PIC code, outline the single modules, and present concepts for implementation on SUPRENUM.     

矢量化采矿工程图纸的应用研究

讨论了利用现代计算机技术处理工程图纸，三种实用的输入方法，针对不同的输入方法，简介了其原理，操作步骤和适用条件，并结合采矿工程图纸的特点进行了评价。     

GIS技术在流域设计径流计算中的应用

以新疆某抽水蓄能电站为例,探索GIS技术在设计径流计算中的应用。首先基于数字高程模型（DEM）和ArcGIS平台提取流域特征信息;然后应用ArcGIS平台,对降水量等值线图和径流等值线图进行矢量化处理（包括图形扫描、图形配准和矢量化等）;最后在ArcGIS平台同时打开流域水系图层、降水量等值线图层和径流深等值线图层。量算两相邻等值线间的流域面积,并采用面积加权法推求流域的降水量和径流深。计算结果表明,GIS技术解决了在等值线图上描绘出设计断面以上流域的问题;解决了因等值线分布不均匀时,如何量算两相邻等值线间的流域面积的问题。     

基于ARM SVE的光滑粒子流体动力学SIMD加速方法

光滑粒子流体动力学（SPH）是近年来兴起的一种无网格的粒子方法,SPH在处理大变形、运动物质表面以及自由表面等问题时优势明显,在数值模拟领域得到了非常广泛的应用,是一种典型的科学计算应用。作为一种显式的粒子方法,SPH在每一个迭代步都需要计算大量的粒子间相互作用,计算量非常大,如何提高SPH的计算效率成为研究热点。可伸缩矢量扩展（SVE）是ARM针对高性能计算推出的下一代SIMD指令集,基于SVE研究了SPH方法的SIMD加速方法,取得了显著的加速效果。     

基于nested阵列的高分辨DOA估计

针对nested阵列对邻近信号的分辨力受信噪比和快拍数等因素限制的问题,提出了基于nested阵列的加权子空间平滑M USIC算法.该算法对协方差矩阵向量化以提高整个阵列的自由度,使用空间平滑恢复新接收数据矢量阵的秩,采用校正的噪声特征值对噪声子空间进行加权,并对信号子空间进行空间谱合成,得到新算法的空间谱函数.通过搜索空间谱函数极大值实现DOA估计.结果表明,该算法在低信噪比及小快拍数条件下,对间隔较近的信号具有高分辨力.     

Improving Memory Traffic by Assembly-Level Exploitation of Reuses for Vector Registers

In this paper, we propose a compilation scheme to analyze and exploit the implicit reuses of vector register data. According to the reuse analysis, we present a translation strategy that translates the vectorized loops into assembly vector codes with exploitation of vector reuses. Experimental results show that our compilation technique can improve the execution time and traffic between shared memory and vector registers. Techniques discussed here are simple, systematic, and easy to be implemented in the conventional vector compilers or translators to enhance the data locality of vector registers.     

面向SLP 的多重循环向量化

如今,越来越多的处理器集成了SIMD(single instruction multiple data)扩展,现有的编译器大多也实现了自动向量化的功能,但是一般都只针对最内层循环进行向量化,对于多重循环缺少一种通用、易行的向量化方法.为此,提出了一种面向SLP(superword level parallelism)的多重循环向量化方法,从外至内依次对各个循环层次进行分析,收集各层循环对应的一些影响向量化效果的属性值,主要包括能否对该循环进行直接循环展开和压紧、有多少数组引用相对于该循环索引连续以及该循环所包含的区域等,然后根据这些属性值决定在哪些循环层次进行直接循环展开和压紧,最后通过SLP对循环中的语句进行向量化.实验结果表明,该算法相对于内层循环向量化和简单的外层循环向量化平均加速比提升了2.13和1.41,对于一些常用的核心循环可以得到高达5.3的加速比.