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Using Parallel Computing for Adaptive Beamforming Applications

Abstract| Recently, smart antenna systems have been widely considered to provide interfer-ence reduction and improve the capacity, data rates, and performance of wireless mobile commu-nication. Smart antenna arrays with adaptive beamforming capability are very e®ective in thesuppression of inter...

Cublas matrix multiplication

Gpu-based parallel computing, NVIDIA official by calling cublas (Basic Linear Algebra Subprograms) library function, and c ++ program to prepare mixed by nvcc compiled, MATLAB called accelerated computing matlab achieve double-precision matrix multiplied under....

Programming the GPU using CUDA platform to multiply matrices

This procedure for simple CUDA programming, both programs is to multiply matrices. Which is the difference between Matrix1 and Matrix2 Matrix2 uses shared memory. Each program using serial and parallel two ways to multiply, eventually will result in parallel and serial computation results, verify th...

bubble sort with parallel computing

Bubble sort is a simple and well-known sortingalgorithm. It is used in practice once in a blue moon and its main applicationis to make an introduction to the sorting algorithms. Bubble sort belongs toO(n2) sorting algorithms, which makes it quite inefficient forsorting large data volumes. Bubble sor...

JAVA multi-threaded parallel computing algorithm for sorting binary insertion

Application backgroundParallel computing is a new technology, but the code for parallel computing is not particularly popular. This article is about the parallel binary insertion sort computing applications, hope to help you learn.Key TechnologyParallel computing, multi thread, binary insertion sort...

OpenCl infrastructure code

Application backgroundPassword violence calculations, large data computing will be used, parallel computing, this routine for the general openCL parallel computing, based on the NVIDIA platform, the routine synthesis of the common functions of the openCL, the platform to create, device selection, me...

CUDA on GPU kMeans

Application backgroundCUDA on the kMeans to achieve GPU, a cluster analysis.We often come into contact with the clustering analysis. It is a common practice to extract N features, and then put them together to form a N vector, so that a mapping from the original data set to a N dimensional vector sp...

CUDA parallel computing

Application backgroundVS_cuda parallel computing two vs based on the realization of the.Cu code to achieve a simple matrix multiplication and inversion....

Examples of OpenMP parallel computing

OpenMP, parallel computing is a very useful way to improve code efficiency;...

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