vote_shared.cuh
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#ifndef STIM_CUDA_VOTE_SHARED_H
#define STIM_CUDA_VOTE_SHARED
# include <iostream>
# include <cuda.h>
#include <stim/cuda/cudatools.h>
#include <stim/cuda/sharedmem.cuh>
#include "cpyToshare.cuh"
namespace stim{
namespace cuda{
// this kernel calculates the vote value by adding up the gradient magnitudes of every voter that this pixel is located in their voting area
template<typename T>
__global__ void cuda_vote(T* gpuVote, T* gpuGrad, T* gpuTable, T phi, int rmax, int x, int y){
//generate a pointer to shared memory (size will be specified as a kernel parameter)
extern __shared__ float s_grad[];
//calculate the start point for this block
int bxi = blockIdx.x * blockDim.x;
// calculate the 2D coordinates for this current thread.
int xi = bxi + threadIdx.x;
int yi = blockIdx.y * blockDim.y + threadIdx.y;
// convert 2D coordinates to 1D
int i = yi * x + xi;
// define a local variable to sum the votes from the voters
float sum = 0;
//calculate the width of the shared memory block
int swidth = 2 * rmax + blockDim.x;
// compute the size of window which will be checked for finding the proper voters for this pixel
int x_table = 2*rmax +1;
int rmax_sq = rmax * rmax;
int tx_rmax = threadIdx.x + rmax;
int bxs = bxi - rmax;
//for every line (along y)
for(int yr = -rmax; yr <= rmax; yr++){
if (yi+yr<y && yi+yr>=0){
//copy the portion of the image necessary for this block to shared memory
__syncthreads();
cpyG2S1D2ch<float>(s_grad, gpuGrad, bxs, yi + yr , 2*swidth, 1, threadIdx, blockDim, x, y);
__syncthreads();
if(xi < x && yi < y){
for(int xr = -rmax; xr <= rmax; xr++){
//find the location of this voter in the atan2 table
int id_t = (yr + rmax) * x_table + xr + rmax;
// calculate the angle between the pixel and the current voter in x and y directions
float atan_angle = gpuTable[id_t];
// calculate the voting direction based on the grtadient direction
int idx_share = xr + tx_rmax ;
float theta = s_grad[idx_share*2];
float mag = s_grad[idx_share*2 + 1];
// check if the current voter is located in the voting area of this pixel.
if (((xr * xr + yr *yr)< rmax_sq) && (abs(atan_angle - theta) <phi)){
sum += mag;
}
}
}
}
}
if(xi < x && yi < y)
gpuVote[i] = sum;
}
template<typename T>
void gpu_vote(T* gpuVote, T* gpuGrad, T* gpuTable, T phi, unsigned int rmax, unsigned int x, unsigned int y){
unsigned int max_threads = stim::maxThreadsPerBlock();
dim3 threads(max_threads, 1);
dim3 blocks(x/threads.x + (x %threads.x == 0 ? 0:1) , y);
// specify share memory
unsigned int share_bytes = (2*rmax + threads.x)*1*2*sizeof(T);
//call the kernel to do the voting
cuda_vote <<< blocks, threads,share_bytes >>>(gpuVote, gpuGrad, gpuTable, phi, rmax, x , y);
}
template<typename T>
void cpu_vote(T* cpuVote, T* cpuGrad,T* cpuTable, T phi, unsigned int rmax, unsigned int x, unsigned int y){
//calculate the number of bytes in the array
unsigned int bytes = x * y * sizeof(T);
//calculate the number of bytes in the atan2 table
unsigned int bytes_table = (2*rmax+1) * (2*rmax+1) * sizeof(T);
//allocate space on the GPU for the Vote Image
T* gpuVote;
cudaMalloc(&gpuVote, bytes);
//allocate space on the GPU for the input Gradient image
T* gpuGrad;
HANDLE_ERROR(cudaMalloc(&gpuGrad, bytes*2));
//copy the Gradient Magnitude data to the GPU
HANDLE_ERROR(cudaMemcpy(gpuGrad, cpuGrad, bytes*2, cudaMemcpyHostToDevice));
//allocate space on the GPU for the atan2 table
T* gpuTable;
HANDLE_ERROR(cudaMalloc(&gpuTable, bytes_table));
//copy the atan2 values to the GPU
HANDLE_ERROR(cudaMemcpy(gpuTable, cpuTable, bytes_table, cudaMemcpyHostToDevice));
//call the GPU version of the vote calculation function
gpu_vote<T>(gpuVote, gpuGrad, gpuTable, phi, rmax, x , y);
//copy the Vote Data back to the CPU
cudaMemcpy(cpuVote, gpuVote, bytes, cudaMemcpyDeviceToHost) ;
//free allocated memory
cudaFree(gpuTable);
cudaFree(gpuVote);
cudaFree(gpuGrad);
}
}
}
#endif