/* * cuCorrTimetime.cu * correlation between two sets of images in time domain */ #include "cuAmpcorUtil.h" template __global__ void cuArraysCorrTime_kernel( const int nImages, const float *templateIn, const int templateNY, const int templateNX, const int templateSize, const float *imageIn, const int imageNY, const int imageNX, const int imageSize, float *resultOut, const int resultNY, const int resultNX, const int resultSize) { __shared__ float shmem[nthreads*(1+NPT)]; const int tid = threadIdx.x; const int bid = blockIdx.x; const int yc = blockIdx.y*NPT; const int imageIdx = bid; const int imageOffset = imageIdx * imageSize; const int templateOffset = imageIdx * templateSize; const int resultOffset = imageIdx * resultSize; const float * imageD = imageIn + imageOffset + tid; const float *templateD = templateIn + templateOffset + tid; float * resultD = resultOut + resultOffset; const int q = min(nthreads/resultNX, 4); const int nt = nthreads/q; const int ty = threadIdx.x / nt; const int tx = threadIdx.x - nt * ty; const int templateNXq = templateNX/q; const int jbeg = templateNXq * ty; const int jend = ty+1 >= q ? templateNX : templateNXq + jbeg; float *shTemplate = shmem; float *shImage = shmem + nthreads; float *shImage1 = shImage + tx; float corrCoeff[NPT]; for (int k = 0; k < NPT; k++) corrCoeff[k] = 0.0f; int iaddr = yc*imageNX; float img[NPT]; for (int k = 0; k < NPT-1; k++, iaddr += imageNX) img[k] = imageD[iaddr]; for (int taddr = 0; taddr < templateSize; taddr += templateNX, iaddr += imageNX) { shTemplate[tid] = templateD[taddr]; img [NPT-1] = imageD[iaddr]; for (int k = 0; k < NPT; k++) shImage[tid + nthreads*k] = img[k]; for (int k = 0; k < NPT-1; k++) img[k] = img[k+1]; __syncthreads(); if (tx < resultNX && ty < q) { #pragma unroll 8 for (int j = jbeg; j < jend; j++) for (int k = 0; k < NPT; k++) corrCoeff[k] += shTemplate[j]*shImage1[j + nthreads*k]; } __syncthreads(); } for (int k = 0; k < NPT; k++) shmem[tid + nthreads*k] = corrCoeff[k]; __syncthreads(); for (int j = tx + nt; j < nthreads; j += nt) for (int k = 0; k < NPT; k++) corrCoeff[k] += shmem[j + nthreads*k]; __syncthreads(); if (tid < resultNX) { int raddr = yc*resultNX + tid; for (int k = 0; k < NPT; k++, raddr += resultNX) if (raddr < resultSize) resultD[raddr] = corrCoeff[k]; } } void cuCorrTimeDomain(cuArrays *templates, cuArrays *images, cuArrays *results, cudaStream_t stream) { /* compute correlation matrix */ const int nImages = images->count; const int imageNX = images->width; const int NPT = 8; const dim3 grid(nImages, (results->width-1)/NPT+1, 1); //fprintf(stderr, "corrTimeDomain %d %d %d\n", imageNX, templates->height, results->height); if (imageNX <= 64) cuArraysCorrTime_kernel< 64,NPT><<>>(nImages, templates->devData, templates->height, templates->width, templates->size, images->devData, images->height, images->width, images->size, results->devData, results->height, results->width, results->size); else if (imageNX <= 128) cuArraysCorrTime_kernel< 128,NPT><<>>(nImages, templates->devData, templates->height, templates->width, templates->size, images->devData, images->height, images->width, images->size, results->devData, results->height, results->width, results->size); else if (imageNX <= 192) cuArraysCorrTime_kernel< 192,NPT><<>>(nImages, templates->devData, templates->height, templates->width, templates->size, images->devData, images->height, images->width, images->size, results->devData, results->height, results->width, results->size); else if (imageNX <= 256) cuArraysCorrTime_kernel< 256,NPT><<>>(nImages, templates->devData, templates->height, templates->width, templates->size, images->devData, images->height, images->width, images->size, results->devData, results->height, results->width, results->size); else if (imageNX <= 384) cuArraysCorrTime_kernel< 384,NPT><<>>(nImages, templates->devData, templates->height, templates->width, templates->size, images->devData, images->height, images->width, images->size, results->devData, results->height, results->width, results->size); else if (imageNX <= 512) cuArraysCorrTime_kernel< 512,NPT><<>>(nImages, templates->devData, templates->height, templates->width, templates->size, images->devData, images->height, images->width, images->size, results->devData, results->height, results->width, results->size); else if (imageNX <= 640) cuArraysCorrTime_kernel< 640,NPT><<>>(nImages, templates->devData, templates->height, templates->width, templates->size, images->devData, images->height, images->width, images->size, results->devData, results->height, results->width, results->size); else if (imageNX <= 768) cuArraysCorrTime_kernel< 768,NPT><<>>(nImages, templates->devData, templates->height, templates->width, templates->size, images->devData, images->height, images->width, images->size, results->devData, results->height, results->width, results->size); else if (imageNX <= 896) cuArraysCorrTime_kernel< 896,NPT><<>>(nImages, templates->devData, templates->height, templates->width, templates->size, images->devData, images->height, images->width, images->size, results->devData, results->height, results->width, results->size); else if (imageNX <= 1024) cuArraysCorrTime_kernel<1024,NPT><<>>(nImages, templates->devData, templates->height, templates->width, templates->size, images->devData, images->height, images->width, images->size, results->devData, results->height, results->width, results->size); else assert(0); getLastCudaError("cuArraysCorrTime error"); }