搜索资源列表
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
cuda_matrix
- 自编的cuda矩阵例子,主要是矩阵运算，适合初学者-cuda matrix code for new learner
array_mul
- 基于CUDA的高维矩阵运算1，计算机本科毕业设计-CUDA-based operator of high-dimensional matrix 1, a computer graduate design
matrixAdd
- 基于CUDA的高维矩阵运算2（加运算），计算机毕业设计-CUDA-based operator of high-dimensional matrix of 2 (plus operator), graduated from the design of computer
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
MatrixMul
- 基于CUDA的高维矩阵运算4，计算机毕业设计-CUDA-based operator of high-dimensional matrix 4, the design of computer graduates
matrixTimes
- 基于CUDA的高维矩阵运算5，计算机毕业设计-CUDA-based operator of high-dimensional matrix of 5, graduated from the design of computer
matrixmult2
- CUDA Fast matrix multiplication and with shared memory.
MMatrix
- Program for mult matrix with CUDA
CUDA-imization
- CUDA稀疏矩阵与矢量乘法的优化CUDA-based sparse matrix vector multiplication optimization-CUDA-based sparse matrix vector multiplication optimization
CUting
- CUDA矩阵乘法和FFT性能测试CUDA matrix multiplication and FFT performance testing-CUDA matrix multiplication and FFT performance testing
matirx-muliplication
- 矩阵相乘，基于CUDA用并行算法实现矩阵的乘法-matrix muliplication with parallel algorithm implication matrix muliplication base on CUDA
Matrix_Mul_limited
- Cuda简单的矩阵乘法程序，用于cuda初学者参考用-Cuda simple matrix multiplication program for beginners reference cuda
matrix-
- C++与Cuda结合，用并行来做加速，将普通的稀疏矩阵加减乘用并行来完成。-C++ and Cuda combined with a parallel acceleration to do, the ordinary addition and subtraction by using sparse matrix parallel to complete.
sum
- Sum matrix in parallel on CUDA
spmv_csr
- 稀疏矩阵的DIA/ELLPACK/COO/CSR/HYB表示形式，以及各表示形式下的稀疏矩阵乘法（稀疏大矩阵*矢量）的CUDA实现。对于矩阵中每一行稀疏元素个数较统一的情况，ELLPACK表示最佳，其次是HYB（ELL+COO）。 CUDA™ 是一种由NVIDIA推出的通用并行计算架构，该架构使GPU能够解决复杂的计算问题。 它包含了CUDA指令集架构（ISA）以及GPU内部的并行计算引擎。 开发人员现在可以使用C语言来为CUDA™ 架构编写程序-Sparse matri
TestMatMul
- 矩阵乘法的源码实现，并结合cuda进行加速，是最基本的cuda编程代码-matrix multiplication and cuda
JCudaMatrixGPU
- 矩阵计算（并行计算，使用cuda），加入计时器-matrix computation(use parallel computation under cuda), add counter of time
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