/* ----------------------------------------------------------------------- Copyright 2012 iMinds-Vision Lab, University of Antwerp Contact: astra@ua.ac.be Website: http://astra.ua.ac.be This file is part of the All Scale Tomographic Reconstruction Antwerp Toolbox ("ASTRA Toolbox"). The ASTRA Toolbox is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. The ASTRA Toolbox is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with the ASTRA Toolbox. If not, see . ----------------------------------------------------------------------- $Id$ */ #include #include #include "util.h" namespace astraCUDA { bool copyVolumeToDevice(const float* in_data, unsigned int in_pitch, const SDimensions& dims, float* outD_data, unsigned int out_pitch) { size_t width = dims.iVolWidth; size_t height = dims.iVolHeight; // TODO: memory order cudaError_t err; err = cudaMemcpy2D(outD_data, sizeof(float)*out_pitch, in_data, sizeof(float)*in_pitch, sizeof(float)*width, height, cudaMemcpyHostToDevice); ASTRA_CUDA_ASSERT(err); assert(err == cudaSuccess); return true; } bool copyVolumeFromDevice(float* out_data, unsigned int out_pitch, const SDimensions& dims, float* inD_data, unsigned int in_pitch) { size_t width = dims.iVolWidth; size_t height = dims.iVolHeight; // TODO: memory order cudaError_t err = cudaMemcpy2D(out_data, sizeof(float)*out_pitch, inD_data, sizeof(float)*in_pitch, sizeof(float)*width, height, cudaMemcpyDeviceToHost); ASTRA_CUDA_ASSERT(err); return true; } bool copySinogramFromDevice(float* out_data, unsigned int out_pitch, const SDimensions& dims, float* inD_data, unsigned int in_pitch) { size_t width = dims.iProjDets; size_t height = dims.iProjAngles; // TODO: memory order cudaError_t err = cudaMemcpy2D(out_data, sizeof(float)*out_pitch, inD_data, sizeof(float)*in_pitch, sizeof(float)*width, height, cudaMemcpyDeviceToHost); ASTRA_CUDA_ASSERT(err); return true; } bool copySinogramToDevice(const float* in_data, unsigned int in_pitch, const SDimensions& dims, float* outD_data, unsigned int out_pitch) { size_t width = dims.iProjDets; size_t height = dims.iProjAngles; // TODO: memory order cudaError_t err; err = cudaMemcpy2D(outD_data, sizeof(float)*out_pitch, in_data, sizeof(float)*in_pitch, sizeof(float)*width, height, cudaMemcpyHostToDevice); ASTRA_CUDA_ASSERT(err); return true; } bool allocateVolume(float*& ptr, unsigned int width, unsigned int height, unsigned int& pitch) { size_t p; cudaError_t ret = cudaMallocPitch((void**)&ptr, &p, sizeof(float)*width, height); if (ret != cudaSuccess) { reportCudaError(ret); fprintf(stderr, "Failed to allocate %dx%d GPU buffer\n", width, height); return false; } assert(p % sizeof(float) == 0); pitch = p / sizeof(float); return true; } void zeroVolume(float* data, unsigned int pitch, unsigned int width, unsigned int height) { cudaError_t err; err = cudaMemset2D(data, sizeof(float)*pitch, 0, sizeof(float)*width, height); ASTRA_CUDA_ASSERT(err); } bool allocateVolumeData(float*& D_ptr, unsigned int& pitch, const SDimensions& dims) { return allocateVolume(D_ptr, dims.iVolWidth, dims.iVolHeight, pitch); } bool allocateProjectionData(float*& D_ptr, unsigned int& pitch, const SDimensions& dims) { return allocateVolume(D_ptr, dims.iProjDets, dims.iProjAngles, pitch); } void zeroVolumeData(float* D_ptr, unsigned int pitch, const SDimensions& dims) { zeroVolume(D_ptr, pitch, dims.iVolWidth, dims.iVolHeight); } void zeroProjectionData(float* D_ptr, unsigned int pitch, const SDimensions& dims) { zeroVolume(D_ptr, pitch, dims.iProjDets, dims.iProjAngles); } template __global__ void reduce1D(float *g_idata, float *g_odata, unsigned int n) { extern __shared__ float sdata[]; unsigned int tid = threadIdx.x; unsigned int i = blockIdx.x*(blockSize*2) + tid; unsigned int gridSize = blockSize*gridDim.x; sdata[tid] = 0; while (i < n) { sdata[tid] += g_idata[i]; i += gridSize; } __syncthreads(); if (blockSize >= 512) { if (tid < 256) { sdata[tid] += sdata[tid + 256]; } __syncthreads(); } if (blockSize >= 256) { if (tid < 128) { sdata[tid] += sdata[tid + 128]; } __syncthreads(); } if (blockSize >= 128) { if (tid < 64) { sdata[tid] += sdata[tid + 64]; } __syncthreads(); } if (tid < 32) { volatile float* smem = sdata; if (blockSize >= 64) smem[tid] += smem[tid + 32]; if (blockSize >= 32) smem[tid] += smem[tid + 16]; if (blockSize >= 16) smem[tid] += smem[tid + 8]; if (blockSize >= 8) smem[tid] += smem[tid + 4]; if (blockSize >= 4) smem[tid] += smem[tid + 2]; if (blockSize >= 2) smem[tid] += smem[tid + 1]; } if (tid == 0) g_odata[blockIdx.x] = sdata[0]; } __global__ void reduce2D(float *g_idata, float *g_odata, unsigned int pitch, unsigned int nx, unsigned int ny) { extern __shared__ float sdata[]; const unsigned int tidx = threadIdx.x; const unsigned int tidy = threadIdx.y; const unsigned int tid = tidy * 16 + tidx; unsigned int x = blockIdx.x*16 + tidx; unsigned int y = blockIdx.y*16 + tidy; sdata[tid] = 0; if (x < nx) { while (y < ny) { sdata[tid] += (g_idata[pitch*y+x] * g_idata[pitch*y+x]); y += 16 * gridDim.y; } } __syncthreads(); if (tid < 128) sdata[tid] += sdata[tid + 128]; __syncthreads(); if (tid < 64) sdata[tid] += sdata[tid + 64]; __syncthreads(); if (tid < 32) { // 32 is warp size volatile float* smem = sdata; smem[tid] += smem[tid + 32]; smem[tid] += smem[tid + 16]; smem[tid] += smem[tid + 8]; smem[tid] += smem[tid + 4]; smem[tid] += smem[tid + 2]; smem[tid] += smem[tid + 1]; } if (tid == 0) g_odata[blockIdx.y * gridDim.x + blockIdx.x] = sdata[0]; } float dotProduct2D(float* D_data, unsigned int pitch, unsigned int width, unsigned int height) { #warning FIX MEMORY ORDER unsigned int bx = (width + 15) / 16; unsigned int by = (height + 127) / 128; unsigned int shared_mem2 = sizeof(float) * 16 * 16; dim3 dimBlock2(16, 16); dim3 dimGrid2(bx, by); float* D_buf; cudaMalloc(&D_buf, sizeof(float) * (bx * by + 1) ); float* D_res = D_buf + (bx*by); // Step 1: reduce 2D from image to a single vector, taking sum of squares reduce2D<<< dimGrid2, dimBlock2, shared_mem2>>>(D_data, D_buf, pitch, width, height); cudaTextForceKernelsCompletion(); // Step 2: reduce 1D: add up elements in vector if (bx * by > 512) reduce1D<512><<< 1, 512, sizeof(float)*512>>>(D_buf, D_res, bx*by); else if (bx * by > 128) reduce1D<128><<< 1, 128, sizeof(float)*128>>>(D_buf, D_res, bx*by); else if (bx * by > 32) reduce1D<32><<< 1, 32, sizeof(float)*32*2>>>(D_buf, D_res, bx*by); else if (bx * by > 8) reduce1D<8><<< 1, 8, sizeof(float)*8*2>>>(D_buf, D_res, bx*by); else reduce1D<1><<< 1, 1, sizeof(float)*1*2>>>(D_buf, D_res, bx*by); float x; cudaMemcpy(&x, D_res, 4, cudaMemcpyDeviceToHost); cudaTextForceKernelsCompletion(); cudaFree(D_buf); return x; } bool cudaTextForceKernelsCompletion() { cudaError_t returnedCudaError = cudaThreadSynchronize(); if(returnedCudaError != cudaSuccess) { fprintf(stderr, "Failed to force completion of cuda kernels: %d: %s.\n", returnedCudaError, cudaGetErrorString(returnedCudaError)); return false; } return true; } void reportCudaError(cudaError_t err) { if(err != cudaSuccess) fprintf(stderr, "CUDA error %d: %s.\n", err, cudaGetErrorString(err)); } }