update_dir_global.cuh
9.26 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
#ifndef STIM_CUDA_UPDATE_DIR_GLOBALD_H
#define STIM_CUDA_UPDATE_DIR_GLOBAL_H
# include <iostream>
# include <cuda.h>
#include <stim/cuda/cudatools.h>
#include <stim/cuda/sharedmem.cuh>
#include <stim/visualization/aabb2.h>
#include <stim/visualization/colormap.h>
#include <math.h>
#include "cpyToshare.cuh"
//#define RMAX_TEST 8
namespace stim{
namespace cuda{
template<typename T>
__global__ void cuda_update_dir(T* gpuDir, T* gpuVote, T* gpuGrad, T* gpuTable, T phi, int rmax, int x, int y){
extern __shared__ T S[];
T* shared_atan = S;
size_t n_table = (rmax * 2 + 1) * (rmax * 2 + 1);
stim::cuda::threadedMemcpy((char*)shared_atan, (char*)gpuTable, sizeof(T) * n_table, threadIdx.x, blockDim.x);
//T* shared_vote = &S[n_table];
//size_t template_size_x = (blockDim.x + 2 * rmax);
//size_t template_size_y = (blockDim.y + 2 * rmax);
//stim::cuda::threadedMemcpy2D((char*)shared_vote, (char*)gpuVote, template_size_x, template_size_y, x, threadIdx.y * blockDim.x + threadIdx.x, blockDim.x * blockDim.y);
int xi = blockIdx.x * blockDim.x + threadIdx.x; //calculate the 2D coordinates for this current thread.
int yi = blockIdx.y * blockDim.y + threadIdx.y;
if(xi >= x || yi >= y) return; //if the index is outside of the image, terminate the kernel
int i = yi * x + xi; //convert 2D coordinates to 1D
float theta = gpuGrad[2*i]; //calculate the voting direction based on the grtadient direction - global memory fetch
stim::aabb2<int> bb(xi, yi); //initialize a bounding box at the current point
bb.insert(xi + ceil(rmax * cos(theta)), ceil(yi + rmax * sin(theta)));
bb.insert(xi + ceil(rmax * cos(theta - phi)), yi + ceil(rmax * sin(theta - phi))); //insert one corner of the triangle into the bounding box
bb.insert(xi + ceil(rmax * cos(theta + phi)), yi + ceil(rmax * sin(theta + phi))); //insert the final corner into the bounding box
int x_table = 2*rmax +1;
int lut_i;
T rmax_sq = rmax * rmax;
T dx_sq, dy_sq;
bb.trim_low(0, 0); //make sure the bounding box doesn't go outside the image
bb.trim_high(x-1, y-1);
int by, bx;
int dx, dy; //coordinate relative to (xi, yi)
T v;
T max_v = 0; //initialize the maximum vote value to zero
T alpha;
int max_dx = bb.low[0];
int max_dy = bb.low[1];
for(by = bb.low[1]; by <= bb.high[1]; by++){ //for each element in the bounding box
dy = by - yi; //calculate the y coordinate of the current point relative to yi
dy_sq = dy * dy;
for(bx = bb.low[0]; bx <= bb.high[0]; bx++){
dx = bx - xi;
dx_sq = dx * dx;
lut_i = (rmax - dy) * x_table + rmax - dx;
alpha = shared_atan[lut_i];
if(dx_sq + dy_sq < rmax_sq && abs(alpha - theta) < phi){
v = gpuVote[by * x + bx]; // find the vote value for the current counter
if(v > max_v){
max_v = v;
max_dx = dx;
max_dy = dy;
}
}
}
}
gpuDir[i] = atan2((T)max_dy, (T)max_dx);
}
// this kernel calculates the voting direction for the next iteration based on the angle between the location of this voter and the maximum vote value in its voting area.
template<typename T>
__global__ void leila_cuda_update_dir(T* gpuDir, T* gpuVote, T* gpuGrad, T* gpuTable, T phi, int rmax, int x, int y){
// calculate the 2D coordinates for this current thread.
int xi = blockIdx.x * blockDim.x + threadIdx.x;
int yi = blockIdx.y * blockDim.y + threadIdx.y;
if(xi >= x || yi >= y) return; //if the index is outside of the image, terminate the kernel
int i = yi * x + xi; // convert 2D coordinates to 1D
float theta = gpuGrad[2*i]; // calculate the voting direction based on the grtadient direction - global memory fetch
gpuDir[i] = 0; //initialize the vote direction to zero
float max = 0; // define a local variable to maximum value of the vote image in the voting area for this voter
int id_x = 0; // define two local variables for the x and y position of the maximum
int id_y = 0;
int x_table = 2*rmax +1; // compute the size of window which will be checked for finding the voting area for this voter
int rmax_sq = rmax * rmax;
int tx_rmax = threadIdx.x + rmax;
float atan_angle;
float vote_c;
int xidx, yidx, yr_sq, xr_sq;
for(int yr = -rmax; yr <= rmax; yr++){
yidx = yi + yr; //compute the index into the image
if (yidx >= 0 && yidx < y){ //if the current y-index is inside the image
yr_sq = yr * yr; //compute the square of yr, to save time later
for(int xr = -rmax; xr <= rmax; xr++){
xidx = xi + xr;
if(xidx >= 0 && xidx < x){
xr_sq = xr * xr;
unsigned int ind_t = (rmax - yr) * x_table + rmax - xr;
// calculate the angle between the voter and the current pixel in x and y directions
atan_angle = gpuTable[ind_t];
//atan_angle = atan2((T)yr, (T)xr);
// check if the current pixel is located in the voting area of this voter.
if (((xr_sq + yr_sq)< rmax_sq) && (abs(atan_angle - theta) <phi)){
vote_c = gpuVote[yidx * x + xidx]; // find the vote value for the current counter
// compare the vote value of this pixel with the max value to find the maxima and its index.
if (vote_c>max) {
max = vote_c;
id_x = xr;
id_y = yr;
}
}
}
}
}
}
unsigned int ind_m = (rmax - id_y) * x_table + (rmax - id_x);
float new_angle = gpuTable[ind_m];
if(xi < x && yi < y)
gpuDir[i] = new_angle;
} //end kernel
// this kernel updates the gradient direction by the calculated voting direction.
template<typename T>
__global__ void cuda_update_grad(T* gpuGrad, T* gpuDir, int x, int y){
// calculate the 2D coordinates for this current thread.
int xi = blockIdx.x * blockDim.x + threadIdx.x;
int yi = blockIdx.y * blockDim.y + threadIdx.y;
if(xi >= x || yi >= y) return;
// convert 2D coordinates to 1D
int i = yi * x + xi;
//update the gradient image with the vote direction
gpuGrad[2*i] = gpuDir[i];
}
template<typename T>
void gpu_update_dir(T* gpuVote, T* gpuGrad, T* gpuTable, 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);
// allocate space on the GPU for the updated vote direction
T* gpuDir;
HANDLE_ERROR( cudaMalloc(&gpuDir, bytes) );
unsigned int max_threads = stim::maxThreadsPerBlock();
//dim3 threads(min(x, max_threads), 1);
//dim3 blocks(x/threads.x, y);
dim3 threads( sqrt(max_threads), sqrt(max_threads) );
dim3 blocks(x/threads.x + 1, y/threads.y + 1);
size_t table_bytes = sizeof(T) * (rmax * 2 + 1) * (rmax * 2 + 1);
//size_t curtain = 2 * rmax;
//size_t template_bytes = sizeof(T) * (threads.x + curtain) * (threads.y + curtain);
size_t shared_mem_req = table_bytes;// + template_bytes;
std::cout<<"Shared Memory required: "<<shared_mem_req<<std::endl;
size_t shared_mem = stim::sharedMemPerBlock();
if(shared_mem_req > shared_mem){
std::cout<<"Error: insufficient shared memory for this implementation of cuda_update_dir()."<<std::endl;
exit(1);
}
//call the kernel to calculate the new voting direction
cuda_update_dir <<< blocks, threads, shared_mem_req>>>(gpuDir, gpuVote, gpuGrad, gpuTable, phi, rmax, x , y);
stim::gpu2image<T>(gpuDir, "dir_david.bmp", x, y, -pi, pi, stim::cmBrewer);
//exit(0);
threads = dim3( sqrt(max_threads), sqrt(max_threads) );
blocks = dim3(x/threads.x + 1, y/threads.y + 1);
//call the kernel to update the gradient direction
cuda_update_grad <<< blocks, threads >>>(gpuGrad, gpuDir, x , y);
//free allocated memory
HANDLE_ERROR( cudaFree(gpuDir) );
}
template<typename T>
void cpu_update_dir(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);
//copy the input vote image to the GPU
HANDLE_ERROR(cudaMemcpy(gpuVote, cpuVote, bytes, cudaMemcpyHostToDevice));
//allocate space on the GPU for the input Gradient image
T* gpuGrad;
HANDLE_ERROR(cudaMalloc(&gpuGrad, bytes*2));
//copy the Gradient 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 update direction function
gpu_update_dir<T>(gpuVote, gpuGrad, gpuTable, phi, rmax, x , y);
//copy the new gradient image back to the CPU
cudaMemcpy(cpuGrad, gpuGrad, bytes*2, cudaMemcpyDeviceToHost) ;
//free allocated memory
cudaFree(gpuTable);
cudaFree(gpuVote);
cudaFree(gpuGrad);
}
}
}
#endif