cost.h
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#include <assert.h>
#include <cuda.h>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#include <stdio.h>
#include <stim/visualization/colormap.h>
#include <sstream>
#include <stim/math/vector.h>
#include <stim/cuda/cudatools/devices.h>
#include <stim/cuda/cudatools/threads.h>
///Cost function that works with the gl-spider class to find index of the item with min-cost.
typedef unsigned char uchar;
texture<uchar, cudaTextureType2D, cudaReadModeElementType> texIn;
float *result;
cudaArray* srcArray;
bool testing = false;
inline void checkCUDAerrors(const char *msg)
{
cudaError_t err = cudaGetLastError();
if (cudaSuccess != err){
fprintf(stderr, "Cuda error: %s: %s.\n", msg, cudaGetErrorString(err) );
exit(1);
}
}
///A virtual representation of a uniform template.
///Returns the value of the template pixel.
///@param x, location of a pixel.
__device__ float Template(int x)
{
if(x < 16/6 || x > 16*5/6 || (x > 16*2/6 && x < 16*4/6)){
return 1.0;
}else{
return 0.0;
}
}
///Find the difference of the given set of samples and the template
///using cuda acceleration.
///@param *result, a pointer to the memory that stores the result.
__global__
void get_diff (float *result)
{
//float* shared = SharedMemory();
__shared__ float shared[16][8];
int x = threadIdx.x + blockIdx.x * blockDim.x;
int y = threadIdx.y + blockIdx.y * blockDim.y;
int x_t = threadIdx.x;
int y_t = threadIdx.y;
//int idx = y*16+x;
int g_idx = blockIdx.y;
float valIn = tex2D(texIn, x, y)/255.0;
float valTemp = Template(x);
shared[x_t][y_t] = abs(valIn-valTemp);
__syncthreads();
for(unsigned int step = blockDim.x/2; step >= 1; step >>= 1)
{
__syncthreads();
if (x_t < step)
{
shared[x_t][y_t] += shared[x_t + step][y_t];
}
__syncthreads();
}
__syncthreads();
for(unsigned int step = blockDim.y/2; step >= 1; step >>= 1)
{
__syncthreads();
if(y_t < step)
{
shared[x_t][y_t] += shared[x_t][y_t + step];
}
__syncthreads();
}
__syncthreads();
if(x_t == 0 && y_t == 0)
result[g_idx] = shared[0][0];
// //result[idx] = abs(valIn);
}
///Initialization function, allocates the memory and passes the necessary
///handles from OpenGL and Cuda.
///@param src, cudaGraphicsResource that handles the shared OpenGL/Cuda Texture
///@param DIM_Y, integer controlling how much memory to allocate.
void initArray(cudaGraphicsResource_t src, int DIM_Y)
{
HANDLE_ERROR(
cudaGraphicsMapResources(1, &src)
);
HANDLE_ERROR(
cudaGraphicsSubResourceGetMappedArray(&srcArray, src, 0, 0)
);
HANDLE_ERROR(
cudaBindTextureToArray(texIn, srcArray)
);
cudaMalloc( (void**) &result, DIM_Y*sizeof(float));
checkCUDAerrors("Memory Allocation Issue 1");
//HANDLE_ERROR(
// cudaBindTextureToArray(texIn, ptr, &channelDesc)
// );
}
///Deinit function that frees the memery used and releases the texture resource
///back to OpenGL.
///@param src, cudaGraphicsResource that handles the shared OpenGL/Cuda Texture
void cleanUP(cudaGraphicsResource_t src)
{
HANDLE_ERROR(
cudaFree(result)
);
HANDLE_ERROR(
cudaGraphicsUnmapResources(1,&src)
);
HANDLE_ERROR(
cudaUnbindTexture(texIn)
);
}
///External access-point to the cuda function
///@param src, cudaGraphicsResource that handles the shared OpenGL/Cuda Texture
///@param DIM_Y, the number of samples in the template.
///@inter temporary paramenter that tracks the number of times cost.h was called.
extern "C"
stim::vec<int> get_cost(cudaGraphicsResource_t src, int DIM_Y)
{
// int minGridSize;
// int blockSize;
// cudaOccupancyMaxPotentialBlockSize(&minGridSize, &blockSize, get_diff, 0, 20*DIM_Y*10);
// std::cout << blockSize << std::endl;
// std::cout << minGridSize << std::endl;
// stringstream name; //for debugging
// name << "Test.bmp";
// dim3 block(4,4);
// dim3 grid(20/4, DIM_Y*10/4);
// int gridSize = (DIM_Y*10*20 + 1024 - 1)/1024;
// dim3 grid(26, 26);
// dim3 grid = GenGrid1D(DIM_Y*10*20);
// stim::gpu2image<float>(result, name.str(), 20,DIM_Y*10,0,1);
// name.clear();
// name << "sample_" << inter << "_" << idx << ".bmp";
// stim::gpu2image<float>(v_dif, name.str(), 20,10,0,1);
//float output[DIM_Y];
float *output;
output = (float* ) malloc(DIM_Y*sizeof(float));
stim::vec<int> ret(0, 0);
float mini = 10000000000000000.0;
int idx = 0;
initArray(src, DIM_Y*8);
dim3 numBlocks(1, DIM_Y);
dim3 threadsPerBlock(16, 8);
get_diff <<< numBlocks, threadsPerBlock >>> (result);
cudaMemcpy(output, result, DIM_Y*sizeof(float), cudaMemcpyDeviceToHost);
for( int i = 0; i<DIM_Y; i++){
// std::cout << output[i] << std::endl;
if(output[i] < mini){
mini = output[i];
idx = i;
}
}
// std::cout << "hello" << std::endl;
//output[idx] = get_sum(result+(16*8*idx));
cleanUP(src);
ret[0] = idx; ret[1] = (int) output[idx];
std::cout << output[idx] << std::endl;
free(output);
return ret;
}