CommodityDataTool1

说明：  Parallel Programming common use code!

说明：  数值模拟空心高斯光束在自由空间中的传输特性(NUMERICAL SIMULATION OF PROPAGATION CHARACTERISTICS OF HOLLOW GAUSSIAN BEAMS IN FREE SPACE)

资源描述一、环境环境：Ubuntu14、Hadoop2.6，Eclipse、NLPIR/ICTCLAS2015等； 二、算法简介： 1、此项目是基于Hadoop2.6进行MapReduce并行开发； 2、此项目是文本分类的文本预处理和文本表示部分，包括分词，去停用词，特征选择和文本表示等（分类算法采用的是随机森林算法，暂时未开放，读者可自行采用Mahout或Weka进行验证）； 3、分词采用的是NLPIR/ICTCLAS2015；文本表示采用的是VSM模型，权重计算采用TFIDF进行文本表示；特征选择采用CHI算法（卡方统计）； 4、关于并行分词环境搭建，可参考我的博客http://www.cnblogs.com/merru/p/4917665.html 5、关于Hadoop环境搭建，可参考我的博客http://www.cnblogs.com/merru/p/4901528.html和http://www.cnblogs.com/merru/p/4905118.html。

CUDA的基礎的矩陣相乘法，包含CPU版本以及GPU版本(CUDA Matrix)

用MPI实现的矩阵乘法的cannon算法，linux平台(matrix multiplication in Cannon method with MPI)

使用CUDA并行语言编写的矩阵乘法，与串行语句的对比试验，主要检测出CPU与GPU运行的时间，通过比较时间，达到比较效果。另外此程序可以随意更改矩阵的维数，增强程序的移植性。(CUDA parallel language use matrix multiplication, and serial statement comparison test, the main test of CPU and GPU to run time, by comparing the time, to compare results. Also this program can change the dimension of the matrix, and enhanced portability of the program.)

This book is for students and researchers who are interested in scientific computation. The book has a dual purpose: first, it is a textbook for a course on parallel scientific computation. Second, the book is a source of example parallel algorithms and programs for computational physicists and chemists, and for other computational scientists who are eager to get a quick start in parallel computing and want to learn a structured approach to writing parallel programs.

CUDA平行的優化，以矩陣乘法為基礎。透過ShareMemory做加速(CUDA ShareMem)

说明：  Hinf use in robust control(robust control)

测绘技能大赛试题03 帮助需要进行比赛的同学解除困难(Question 03 of Surveying and Mapping Skills Competition)