Please, have a look at our wiki page https://github.com/OrangeOwlSolutions/General-CUDA-programming/wiki

CUDA codes

• Folder simpleExamples: codes for course Introduction to GPU computing with CUDA.

• Folder coalescence: codes for course Introduction to GPU computing with CUDA.

• Folder shared memory: codes for course Introduction to GPU computing with CUDA.

• Reductions.cu: different kinds of reductions, including reduction without__syncthreads, reduction with no deadlock, atomic warp reduction and threadfence reduction, see ???;

• Multiple1DMovingAveragesShared.cu: performing several 1d moving averages in parallel, see Performing several 1D moving averages in parallel using CUDA;

• SurfaceMemory.cu: simple example on how using CUDA surface memory to write to a texture memory, see Texture memory with READ and WRITE;

• 1DMovingAveragePeriodicBoundaryTexture.cu: showing how a median filter can be easily implemented on a signal having periodic boundary using CUDA textures, see Dealing with boundary conditions in CUDA;

• cudaMallocPitch_and_cudaMemcpy2D.cu: showing how using cudaMallocPitch to allocate 2D arrays and how moving 2D data from/to host memory to/from global memory allocated with cudaMallocPitch using cudaMemcpy2D, see cudaMallocPitch and cudaMemcpy2D;

• WriteToCUDATextureAcrossKernels.cu: writing to a CUDA texture across different kernel launches, see Writing to a CUDA texture across kernels;

• AddressingModesCUDATextures.cu: the different types of addressing modes of a CUDA texture, see The different addressing modes of CUDA textures;

• Meshgrid.cu: Emulating Matlab's meshgrid in CUDA, see Replicate a vector multiple times using CUDA Thrust;

• ReverseArray.cu: Reversing the order of the elements within an array, see ???;