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数据结构实验
多种算法实现链表的排序,可以更具需要进行适当该表计算哦,是基础了,欢迎同在学习的伙伴一起努力哦~
数据结构实验
- 2022-11-12 13:15:04下载
- 积分:1
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利用CUDA平台计算矩阵乘法的GPU编程
本程序为简易的CUDA编程,两个程序都是计算矩阵的乘法。其中Matrix1和Matrix2的区别是Matrix2使用了shared memory。每个程序都使用了串行和并行两种方式计算乘法,最后将并行的运算结果与串行运算结果对比,验证计算的正确性。同时,程序中利用CUDA计时模块统计了并行运算的耗时。因此可以得出使用shared memory后改善的运行时间。
- 2022-12-18 17:50:03下载
- 积分:1
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bnb20
优化matlab,toolbox,可以用于各种优化问题(Optimization matlab, toolbox, can be used for a variety of optimization problems)
- 2008-12-29 23:03:51下载
- 积分:1
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code-of-ugupdate-for-Isight-in-MDO
在Isight环境中集成UG/ANSYS,将UG的prt文件先储存文x_t格式文件,然后再导入ANSYS计算,将实现一个ugupdate.exe,功能除了更新prt文件文还将prt文件另存为x_t文件,以供ANSYS调用。(The Isight environment integrated the UG/ANSYS, the UG prt files first to store text x_t format file, and then import the ANSYS calculation will achieve a ugupdate.exe, functions in addition to updated prt files text will prt files saved as files x_t, for ANSYS invoked.)
- 2012-12-11 16:02:37下载
- 积分:1
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DSP_MATLAB
主要用于微波光子处理的算法优化程序,希望能对各位有所帮助,请放心下载。(aghgdfdasggahdfgdfhhafdfdhfdf)
- 2009-10-11 18:41:33下载
- 积分:1
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GuardedCommandLanguageCompiler0.8.12
并行计算研究基础语言, 含Windows下的编译器(Parallel Computing basic for communication)
- 2018-08-03 18:42:34下载
- 积分:1
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mpi-bitonic-sort-master
Bitonic order implementation code with mpi usage
- 2017-06-06 20:10:50下载
- 积分:1
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mpi
一个用c写的机遇MPI的并行程序,程序实现了求积分的功能(with a c MPI the opportunity to write parallel programs, procedures for the realization of the functional integration)
- 2005-07-14 13:51:47下载
- 积分:1
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求矩阵特征值的并行算法的实现
QR算法是目前最广泛被用于求一般矩阵特征值的方法,但是由于串行算法的时间过于长,大大的降低了工作效率,所以我们将其在基于cuda架构上对其进行GPU加速,将原有的求矩阵特征值得串行算法进行并行化,大大地提高了工作效率
- 2022-11-06 08:40:04下载
- 积分:1
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www
一本将基于近邻传播算法的半监督聚类的算方法书.对于聚类研究的很有帮助(Abstract: A semi-supervised clustering method based on affinity propagation (AP) algorithm is proposed in this
paper. AP takes as input measures of similarity between pairs of data points. AP is an efficient and fast clustering
algorithm for large dataset compared with the existing clustering algorithms, such as K-center clustering. But for the
datasets with complex cluster structures, it cannot produce good clustering results. It can improve the clustering
performance of AP by using the priori known labeled data or pairwise constraints to adjust the similarity matrix.
Experimental results show that such method indeed reaches its goal for complex datasets, and this method
outperforms the comparative methods when there are a large number of pairwise constraints. )
- 2011-07-09 11:40:46下载
- 积分:1