Graph‐Theory Approach to Eigenvalue Problem of Large Space Structures

The dynamic analysis and control system design of large space structures involve the solution of the large‐dimensional generalized matrix eigenvalue problem. The computational effort involved is proportional to the third power of the dimension of the matrices involved. To minimize the computational time a graph‐theory approach to reduce a matrix to lower‐ordered submatrices is proposed. The matrix‐reduction algorithm uses the Boolean matrices corresponding to the original numerical matrices and, thus, the computational effort to reduce the original matrix is nominal. The computational savings directly depend upon the number of submatrices into which the original matrix is reduced. A free‐free square plate is considered as an example to illustrate the technique. In this example a matrix of 16th order is reduced to three scalars corresponding to three rigid‐body modes, and three matrices of order three and one matrix of order four.     

基于图形化编程语言LabVIEW的虚拟仪器开发

本文介绍了虚拟仪器的概念，组成特征和图形化编程语言LabVIEW，并用LabVIEW开发了位移测试和系统静态精度测试系统。     

Adaptive block size for dense QR factorization in hybrid CPU–GPU systems via statistical modeling

QR factorization is a computational kernel of scientific computing. How can the latest computer be used to accelerate this task? We investigate this topic by proposing a dense QR factorization algorithm with adaptive block sizes on a hybrid system that contains a central processing unit (CPU) and a graphic processing unit (GPU). To maximize the use of CPU and GPU, we develop an adaptive scheme that chooses block size at each iteration. The decision is based on statistical surrogate models of performance and an online monitor, which avoids unexpected occasional performance drops. We modify the highly optimized CPU–GPU based QR factorization in MAGMA to implement the proposed schemes. Numerical results suggest that our approaches are efficient and can lead to near-optimal block sizes. The proposed algorithm can be extended to other one-sided factorizations, such as LU and Cholesky factorizations.     

基于CUDA的并行粒子群优化算法研究及实现

应用图形处理器(GPU)来加速粒子群优化(PSO)算法并行计算时,为突出其加速性能,经常有文献以恶化CPU端PSO算法性能为代价。为了科学比较GPU-PSO算法和CPU-PSO算法的性能,提出用"有效加速比"作为算法的性能指标。文中给出的评价方法不需要CPU和GPU端粒子数相同,将GPU并行算法与最优CPU串行算法的性能作比较,以加速收敛到目标精度为准则,在统一计算设备架构(CUDA)下对多个基准测试函数进行了数值仿真实验。结果表明,在GPU上大幅增加粒子数能够加速PSO算法收敛到目标精度,与CPU-PSO相比,获得了10倍以上的"有效加速比"。     

“里特罗”风格与平面设计

“里特罗”风格的设计流派的特点是强调历史风格的复古和重构,是对欧洲20世纪上半叶的平面设计风格的复兴。“里特罗”风格既是对这个时期的风格特点的偏爱和认可,又是对当时的现代主义和国际主义中的沉闷、刻板、乏味以及过分理性的反对。由于这个风格是对20世纪20年代至30年代流行的某些平面风格的复兴及演绎,对于今天的平面设计依然有着重要的影响。     

关于AUTO CAD在图形图像教学领域的多元结合应用

AUTO CAD是一款交互式计算机辅助设计以及绘图的软件,在传统的教学中很多学生都认为这款软件的学习十分困难,所以很难提起学习兴趣,还有一些学生学习了后面的知识就会忘记前面的知识,这就使得教学质量与效率很难提升。为此,教师应积极主动探索有效的教学方式,激发学生的ATUO CAD软件的学习兴趣,提升教学和学习的质量。本文就探讨ATUO CAD在图形图像教学领域的多元结合应用。     

工程设备图形化管理系统的程序设计

介绍工程设备图形化数据库管理系统设计的一般方法和技术，分析和实施将设备对象作为图形对象处理时的程序设计技术，重点叙述图形对象与数据库关联的面向对象的程序设计方法。     

浅论平面设计软件在中职艺术类院校的运用

本文通过探讨平面设计软件在中职艺术类院校的运用,提出了如何让学生在有限的时间里快速掌握多种平面广告设计软件的途径,对中职学生如何学好平面广告设计课程做出了一些思考。     

软件本地化中图形界面设计

跨国化的软件和网站设计需要本地化,本地化的界面设计强调文化对目标用户的影响.除了文字翻译,根据本地文化和传统对界面的布局和图形进行调整也是必须的,并且成为产品成败的重要因素之一.