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2D CUDA-based bilinear interpolation
- This MEX performs 2d bilinear interpolation using an NVIDIA graphics chipset. To compile and run this software, one needs the NVIDIA CUDA Toolkit (http://www.nvidia.com/object/cuda_get.html) and, of course, an NVIDIA graphics card of reasonably moder
dct8x8.rar
- cuda开发环境下的矩阵运算，cuda sdk中的内容，矩阵运算充分显示了并行编程的优势，对于学习cuda编程有着很好的借鉴作用,matrix operations in parallel with cuda platform
matrixMul
- GPU CUDA的经典算法，基于shared memory进行矩阵的相乘运算-GPU CUDA classical algorithm, based on shared memory for matrix multiplication by
juzhen
- cuda矩阵乘法的源代码。（注：需要cuda平台）-cuda matrix multiplication of the source code. (Note: the need for cuda platform)
CUDA-example
- 包括矩阵相乘，转置，快速傅里叶变换，多GPU编程等23个实例-Including matrix multiplication, transposition, fast Fourier transform, multi-GPU programming in 23 instances
matrixMul
- 采用GPU通用计算API（CUDA）实现矩阵相乘。-The use of general-purpose GPU computing API (CUDA) to achieve the matrix multiplication.
transpose
- cuda平台开发的矩阵变换并行操作（Matrix transpose），属于cuda sdk中的内容-Small Matrix transpose with Cuda (Example for a 16x16 matrix)
mv
- cuda Faster Matrix-Vector Multiplication on GeForce 8800GTX
matrixInverse
- 基于CUDA的高维矩阵运算3，计算机毕业设计-CUDA-based operator of high-dimensional matrix 3, the design of computer graduates
cuda_matmult_opt
- CUDA matrix multiplication 3 different optimization schemes are included (loop unrolling, data prefetching, thread granularity)
matrixMul
- a cuda program for parallel multiplication of matrix
matrixmult2
- CUDA Fast matrix multiplication and with shared memory.
MMatrix
- Program for mult matrix with CUDA
MatrixMul
- an example of matrix multipication on cuda GPU
matrixMul
- cuda 矩阵运算程序，cuda上实现两个矩阵相乘-cuda matrix multi
cuda+mpi
- 并行计算中矩阵相乘的mpi和cuda两种方法，已完成检验，有结果输出(In parallel computing, two methods of matrix multiplication, MPI and CUDA, have been tested and output with results)
matrix multiply
- Matrix multiply on cuda GPU
CUDA SPMV
- 稀疏矩阵向量乘法（Sparse Matrix-Vector Multiplication, SpMV）在许多科学计算程序中都有广泛的应用。数据矩阵A 是稀疏的，输入向量x 和输出向量y是稠密的。 y = Ax(Sparse Matrix-Vector Multiplication (SpMV) is widely used in many scientific computing programs. The data matrix A is sparse, the input vector x
Matrix-Inversion-with-CUDA-master
- 利用cuda完成GPU编程，实现对给定矩阵的求逆操作(a cuda code for calculating a inverse matrix of a given matrix)
GPU高性能编程CUDA实战—示例代码
- 结合GPU高性能编程，提供实战样例程序，包含矩阵乘法，原子操作，热传导，多GPU，多流的代码(Combined with GPU high performance programming, it provides actual sample program, including matrix multiplication, atomic operation, heat conduction, multi GPU, and multi stream code.)