搜索资源列表
Matrix
- 矩阵相乘并行计算程序 C——C++边写 已实现-Matrix multiplication parallel program
MatrixMultiplication_OpenCL
- 矩阵相乘并行计算方法，基于OPENCL通用计算接口。-Parallel matrix multiplication calculation method, based OPENCL general computing interface.
matrix
- 矩阵相乘并行算法MPI源程序 并行思想加快速度-MPI parallel matrix multiplication algorithm source code parallel thinking speed
summa
- 矩阵相乘的SUMMA算法的并行实现，包含了实验结果演示。-SUMMA matrix multiplication algorithm for parallel implementation, including the experimental results presentation.
Matrix-1
- opencl 并行矩阵相乘计算，可以选择AMD与 NVIDIA的GPU进行计算，并且具有计算串行与并行的时间比-opencl parallel matrix multiplication calculations, you can choose AMD and NVIDIA gpu
Matrix
- 这是矩阵相乘的并行代码，opencl写的对于初学opencl语言的人的一个很好的例子。-This is a matrix multiplication parallel code, opencl written language for a good beginner opencl human examples.
opencl-book-samples-read-only
- 《OpenCL编程指南》源代码，书中提供了一系列经典的案例，如图像直方图、Sobel边界检测过滤器、并行实现Dijkstra单源最短路 径图算法、Bullet Physics SDK中的布模拟、用快速傅里叶变换模拟海洋、 光流、OpenCL与PyOpenCL结合使用，使用OpenCL完成矩阵相乘与稀疏矩阵矢 量乘法等-《OpenCL Programming Guide》source code
MPI
- 使用MPI并行编程，矩阵相乘程序测试及 LAPACK 的使用-The use of MPI parallel programming, matrix multiplication program testing and the use of LAPACK
cuda-matrixmul--reverse
- cuda并行计算 两基于vs实现的.cu代码 简单的实现矩阵相乘和反转。-Cuda parallel computing based on vs. Two cu code simple implementation of matrix multiplication and inversion
MPI
- MPI并行实现矩阵相乘，结果输出到txt文件中，可成功运行-MPI parallel implementation of matrix multiplication algorithm, the results of the txt file, can be successfully run.
spark-logisticregression-and-softmax
- spark平台上的机器学习算法，包括分类、回归以及矩阵相乘的并行实现-Machine learning algorithms spark platforms, including classification, regression and parallel implementation of matrix multiplication
MPI_OpenMP_code
- 压缩包里包含几个用C编写的并行代码，运行无误。其中包括，电路满足性的MP程序，floyd算法MPI代码，Sieve_Eratoshenes筛法MPI代码，矩阵相乘的MPI代码以及计算PI值的OpenMP代码。-Which contains several parallel programs written in C to run correctly. Among them, including Floyd algorithm procedures, matrix multiplication M
thqrtest
- 在MPI上实现的矩阵相乘并行计算的源程序,()
pycuda-2017.1.1.tar
- 矩阵相乘的并行运算的算法，运算效率可以轻松提高近100倍。是进行人工智能研究及深度学习先关研究的必备并行算法。(The algorithm of parallel operation of matrix multiplication can easily increase the operation efficiency by nearly 100 times. It is a necessary parallel algorithm for the study of artificial in