intel编译器注册表

并联机构外文资料，parallel mechanisms (PMs) have attracted a lot of attention from the academic and industrial communities. Compared with the more commonly used serial robots, the parallel one has attractive advantages in accuracy, rigidity, capacity, and load-to-weight ratio. The PMs have been and are being used in a wide variety of applications such as motion simulators, parallel manipulators, nanomanipulators, and micro-manipulators. In recent years, the research and application have evolved from general six-DOF PMs to lower-mobility PMs. The essential reason is that lower-mobility PMs have similar applications to general six-DOF PMs, while they are much simpler in structure and cheaper in cost. The research of lower-mobility PMs has become new hot point. A great deal of research on lowermobility PM has been carried out all over the world, and a large number of new mechanisms, such as Delta, Tricept, and medical robots, have been built for various applications.

Intel最新版本的并行开发工具包，包含并行C++编译器icc和并行Fortran编译器ifort，以及相关的Intel并行函数库。 网盘目录下有三个文件： Intel Parallel Studio XE Cluster Edition 2020 x64.rar（Windows版） Intel Parallel Studio XE Cluster Edition 2020 Linux.zip（Linux版） Intel Parallel Studio XE All Licenses.zip（License文件）

INTEL PARALLE STUDIO 2015的破解文件，适用于windows及linux平台 使用方式： 1. 启动程序 2. 安装时选择使用其他方式验证license 3. 选择文件验证方式

Intel Parallel Studio XE 2018破解版，内含lic, 此资源仅供学习使用，请支持正版

This paper presents an algorithm for the determination of the workspace of parallel manipulators. The method described here, which is based on geometrical properties of the workspace, leads to a simple graphical representation of the regions of the three-dimensional Cartesian space that are attainable by the manipulator with a given orientation of the platform. Moreover, the volume of the workspace can be easily computed by performing an integration in its boundary, which is obtained from the algorithm. Examples are included to illustrate the application of the method to a six-degree-of-freedom fully parallel manipulator.

并行编程（CUDA、openMP、MPI） 介绍 这个存储库包含一些并行编程的实现。 使用了 3 种技术：* 用于共享内存拓扑的 openMP * 用于分布式内存拓扑的 openMPI * 用于 GPU（图形处理单元）的 CUDA 项目一 描述 该项目包含使用 openMP 和 openMPI 的线性系统高斯算法的并行化实现，并比较各种并行实现与串行实现之间的并行化和时间增益。 在文件 LU_serial.c 中，已经给出了原始序列号。 使用 openMPI 的算法有 4 个并行实现，它们在数据分配类型和进程之间的通信类型方面有所不同。 第一种类型的数据分配是连续块分配。 因此，如果我们有一个 100x100 元素和 n 个进程的数组，则该数组的前 100/n 行分配给第一个进程，接下来的 100/n 行分配给下一个进程。 第二种数据分配类型是数据的循环分配。 所以，如果我们有一个 10

因特尔并行开发套件的授权文件 版本 intel parallel XE 2013 SP1 Update3

使用MPI计算的完整的PSRS（并行排序(parallel sorting by regular sampling)）代码。并行计算课实验所用代码。

intel_parallel_studio_xe_2013_update_3的license文件