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tile_processor_gpu
Commit 75fa734d authored by Andrey Filippov's avatar Andrey Filippov
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adding more to correlation

parent bbcae7a3
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Showing with 132 additions and 263 deletions
src/TileProcessor.cuh
View file @ 75fa734d
......@@ -815,7 +815,7 @@ __device__ void tile_combine_rgba(
// boolean diff_gauss, // when averaging images, use gaussian around average as weight (false - sharp all/nothing)
float min_agree, // minimal number of channels to agree on a point (real number to work with fuzzy averages)
float * chn_weights, // color channel weights, sum == 1.0
int dust_remove, // Do not reduce average weight when only one image differes much from the average
int dust_remove, // Do not reduce average weight when only one image differs much from the average
int keep_weights, // eturn channel weights and rms after A in RGBA (weight are always calculated, not so for the crms)
int debug);
......@@ -1003,7 +1003,8 @@ extern "C" __global__ void correlate2D(
/**
* Calculate 2D phase correlation pairs from CLT representation. This is an inner kernel that is called
* from correlate2D. If called from the CPU: <<<ceil(number_of_tiles/32),32>>>
* from correlate2D. If called from the CPU: <<<ceil(number_of_tiles/32),32>>>.
* If corr_radius==0, skip normalization and inverse transform, output transform domain tiles
*
* @param gpu_clt array of NUM_CAMS pointers to the CLT (frequency domain) data [TILES-Y][TILES-X][NUM_COLORS][DTT_SIZE*DTT_SIZE]
* @param colors number of colors used: 3 for RGB or 1 for monochrome
......@@ -1014,7 +1015,7 @@ extern "C" __global__ void correlate2D(
* @param num_corr_tiles number of correlation tiles to process
* @param gpu_corr_indices packed array (each element, integer contains tile+pair) of correlation tasks
* @param corr_stride, stride (in floats) for correlation outputs.
* @param corr_radius, radius of the output correlation (maximal 7 for 15x15)
* @param corr_radius, radius of the output correlation (maximal 7 for 15x15). If 0 - output Transform Domain tiles, no normalization
* @param gpu_corrs) allocated array for the correlation output data (each element stride, payload: (2*corr_radius+1)^2
*/
extern "C" __global__ void correlate2D_inner(
......@@ -1028,7 +1029,7 @@ extern "C" __global__ void correlate2D_inner(
int * gpu_corr_indices, // packed tile+pair
const size_t corr_stride, // in floats
int corr_radius, // radius of the output correlation (7 for 15x15)
float * gpu_corrs) // correlation output data
float * gpu_corrs) // correlation output data (either pixel domain or transform domain
{
float scales[3] = {scale0, scale1, scale2};
int corr_in_block = threadIdx.y;
......@@ -1136,109 +1137,129 @@ extern "C" __global__ void correlate2D_inner(
#endif
} // if (color == 1){ // LPF only after B (nothing in mono)
} // for (int color = 0; color < colors; color++){
normalizeTileAmplitude(
clt_corr, // float * clt_tile, // [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports
fat_zero); // float fat_zero ) // fat zero is absolute, scale it outside
// Low Pass Filter from constant area (is it possible to replace?)
// Skip normalization, lpf, inverse correction and unfolding if Transform Domain output is required
if (corr_radius > 0) {
normalizeTileAmplitude(
clt_corr, // float * clt_tile, // [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports
fat_zero); // float fat_zero ) // fat zero is absolute, scale it outside
// Low Pass Filter from constant area (is it possible to replace?)
#ifdef DBG_TILE
#ifdef DEBUG6
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
printf("\ncorrelate2D CORRELATION NORMALIZED, fat_zero=%f\n",fat_zero);
debug_print_clt1(clt_corr, -1, 0xf);
}
__syncthreads();// __syncwarp();
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
printf("\ncorrelate2D CORRELATION NORMALIZED, fat_zero=%f\n",fat_zero);
debug_print_clt1(clt_corr, -1, 0xf);
}
__syncthreads();// __syncwarp();
#endif
#endif
#ifdef DBG_TILE
#ifdef DEBUG6
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
printf("\ncorrelate2D LPF\n");
debug_print_lpf(lpf_corr);
}
__syncthreads();// __syncwarp();
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
printf("\ncorrelate2D LPF\n");
debug_print_lpf(lpf_corr);
}
__syncthreads();// __syncwarp();
#endif
#endif
float *clt = clt_corr + threadIdx.x;
float *clt = clt_corr + threadIdx.x;
#pragma unroll
for (int q = 0; q < 4; q++){
float *lpf = lpf_corr + threadIdx.x;
for (int q = 0; q < 4; q++){
float *lpf = lpf_corr + threadIdx.x;
#pragma unroll
for (int i = 0; i < DTT_SIZE; i++){
(*clt) *= (*lpf);
clt += DTT_SIZE1;
lpf += DTT_SIZE;
for (int i = 0; i < DTT_SIZE; i++){
(*clt) *= (*lpf);
clt += DTT_SIZE1;
lpf += DTT_SIZE;
}
}
}
__syncthreads();// __syncwarp();
__syncthreads();// __syncwarp();
#ifdef DBG_TILE
#ifdef DEBUG6
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
printf("\ncorrelate2D CORRELATION LPF-ed\n");
debug_print_clt1(clt_corr, -1, 0xf);
}
__syncthreads();// __syncwarp();
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
printf("\ncorrelate2D CORRELATION LPF-ed\n");
debug_print_clt1(clt_corr, -1, 0xf);
}
__syncthreads();// __syncwarp();
#endif
#endif
dttii_2d(clt_corr);
dttii_2d(clt_corr);
#ifdef DBG_TILE
#ifdef DEBUG6
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 4)){
printf("\ncorrelate2D AFTER HOSIZONTAL (VERTICAL) PASS, corr_radius=%d\n",corr_radius);
debug_print_clt1(clt_corr, -1, 0xf);
}
__syncthreads();// __syncwarp();
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 4)){
printf("\ncorrelate2D AFTER HOSIZONTAL (VERTICAL) PASS, corr_radius=%d\n",corr_radius);
debug_print_clt1(clt_corr, -1, 0xf);
}
__syncthreads();// __syncwarp();
#endif
#endif
corrUnfoldTile(
corr_radius, // int corr_radius,
(float *) clt_corr, // float* qdata0, // [4][DTT_SIZE][DTT_SIZE1], // 4 quadrants of the clt data, rows extended to optimize shared ports
(float *) mclt_corr); // float* rslt) // [DTT_SIZE2M1][DTT_SIZE2M1]) // 15x15
corrUnfoldTile(
corr_radius, // int corr_radius,
(float *) clt_corr, // float* qdata0, // [4][DTT_SIZE][DTT_SIZE1], // 4 quadrants of the clt data, rows extended to optimize shared ports
(float *) mclt_corr); // float* rslt) // [DTT_SIZE2M1][DTT_SIZE2M1]) // 15x15
__syncthreads();
__syncthreads();
#ifdef DBG_TILE
#ifdef DEBUG6
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
printf("\ncorrelate2D after UNFOLD, corr_radius=%d\n",corr_radius);
debug_print_corr_15x15(
corr_radius, // int corr_radius,
mclt_corr,
-1);
}
__syncthreads();// __syncwarp();
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
printf("\ncorrelate2D after UNFOLD, corr_radius=%d\n",corr_radius);
debug_print_corr_15x15(
corr_radius, // int corr_radius,
mclt_corr,
-1);
}
__syncthreads();// __syncwarp();
#endif
#endif
// copy 15x15 tile to main memory (2 * corr_radius +1) x (2 * corr_radius +1)
int size2r1 = 2 * corr_radius + 1;
int len2r1x2r1 = size2r1 * size2r1;
int corr_tile_offset = + corr_stride * corr_num;
float *mem_corr = gpu_corrs + corr_tile_offset;
// copy 15x15 tile to main memory (2 * corr_radius +1) x (2 * corr_radius +1)
int size2r1 = 2 * corr_radius + 1;
int len2r1x2r1 = size2r1 * size2r1;
int corr_tile_offset = + corr_stride * corr_num;
float *mem_corr = gpu_corrs + corr_tile_offset;
#pragma unroll
// for (int offs = threadIdx.x; offs < DTT_SIZE2M1*DTT_SIZE2M1; offs+=CORR_THREADS_PER_TILE){ // variable number of cycles per thread
for (int offs = threadIdx.x; offs < len2r1x2r1; offs+=CORR_THREADS_PER_TILE){ // variable number of cycles per thread
mem_corr[offs] = mclt_corr[offs];
}
// for (int offs = threadIdx.x; offs < DTT_SIZE2M1*DTT_SIZE2M1; offs+=CORR_THREADS_PER_TILE){ // variable number of cycles per thread
for (int offs = threadIdx.x; offs < len2r1x2r1; offs+=CORR_THREADS_PER_TILE){ // variable number of cycles per thread
mem_corr[offs] = mclt_corr[offs];
}
__syncthreads();
__syncthreads();
#ifdef DBG_TILE
#ifdef DEBUG6
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
printf("\ncorrelate2D after copy to main memory\n");
// debug_print_clt1(clt_corr, -1, 0xf);
}
__syncthreads();// __syncwarp();
if ((tile_num == DBG_TILE) && (corr_pair == 0) && (threadIdx.x == 0)){
printf("\ncorrelate2D after copy to main memory\n");
// debug_print_clt1(clt_corr, -1, 0xf);
}
__syncthreads();// __syncwarp();
#endif
#endif
} else { // if (corr_radius > 0) { transform domain output
// int corr_tile_offset = + corr_stride * corr_num;
float *mem_corr = gpu_corrs + corr_stride * corr_num + threadIdx.x;
float *clt = clt_corr + threadIdx.x;
#pragma unroll
for (int q = 0; q < 4; q++){
#pragma unroll
for (int i = 0; i < DTT_SIZE; i++){
(*mem_corr) = (*clt);
clt += DTT_SIZE1;
mem_corr += DTT_SIZE;
}
}
__syncthreads();// __syncwarp();
} // if (corr_radius > 0) ... else
}
/**
......@@ -1791,6 +1812,7 @@ __global__ void create_nonoverlap_list(
/**
* Helper kernel for correlate2D() - generates dense list of correlation tasks.
* With the quad camera each tile may generate up to 6 pairs (int array elements)
* Tiles are not ordered, but the correlation pairs for each tile are
*
* @param gpu_tasks array of per-tile tasks (struct tp_task)
* @param num_tiles number of tiles int gpu_tasks array prepared for processing
......@@ -2072,7 +2094,7 @@ extern "C" __global__ void textures_nonoverlap(
create_nonoverlap_list<<<blocks0,threads0>>>(
gpu_tasks, // struct tp_task * gpu_tasks,
num_tiles, // int num_tiles, // number of tiles in task
num_tilesx, // int width, // number of tiles in a row
num_tilesx, // int width, // number of tiles in a row
gpu_texture_indices, // int * nonoverlap_list, // pointer to the calculated number of non-zero tiles
pnum_texture_tiles); // int * pnonoverlap_length) // indices to gpu_tasks // should be initialized to zero
cudaDeviceSynchronize();
......@@ -2401,8 +2423,6 @@ extern "C" __global__ void textures_accumulate( // (8,4,1) (N,1,1)
__syncthreads(); // _syncthreads();1
// return either only 4 slices (RBGA) or all 12 (with weights and rms) if keep_weights
// float rgbaw [NUM_COLORS + 1 + NUM_CAMS + NUM_COLORS + 1][DTT_SIZE2][DTT_SIZE21];
// size_t texture_tile_offset = + tile_indx * texture_stride;
......@@ -3805,7 +3825,7 @@ __device__ void tile_combine_rgba(
float * port_offsets, // [port]{x_off, y_off} - just to scale pixel value differences
// int port_mask, // which port to use, 0xf - all 4 (will modify as local variable)
float diff_sigma, // pixel value/pixel change
float diff_threshold,// pixel value/pixel change
float diff_threshold,// pixel value/pixel change - never used
// next not used
// boolean diff_gauss, // when averaging images, use gaussian around average as weight (false - sharp all/nothing)
float min_agree, // minimal number of channels to agree on a point (real number to work with fuzzy averages)
......@@ -3817,7 +3837,7 @@ __device__ void tile_combine_rgba(
float * alpha = rgba + (colors * (DTT_SIZE2*DTT_SIZE21));
float * port_weights = alpha + (DTT_SIZE2*DTT_SIZE21);
float * crms = port_weights + NUM_CAMS*(DTT_SIZE2*DTT_SIZE21); // calculated only if keep_weights
float threshold2 = diff_sigma * diff_threshold;
float threshold2 = diff_sigma * diff_threshold; // never used?
threshold2 *= threshold2; // squared to compare with diff^2
float pair_dist2r [NUM_CAMS*(NUM_CAMS-1)/2]; // new double [ports*(ports-1)/2]; // reversed squared distance between images - to be used with gaussian. Can be calculated once !
int pair_ports[NUM_CAMS*(NUM_CAMS-1)/2][2]; // int [][] pair_ports = new int [ports*(ports-1)/2][2];
......
src/test_tp.cu
View file @ 75fa734d
......@@ -42,12 +42,9 @@
#include <iterator>
#include <vector>
//#include "dtt8x8.cuh"
#include "dtt8x8.h"
#include "geometry_correction.h"
#include "TileProcessor.cuh"
///#include "cuda_profiler_api.h"
//#include "cudaProfiler.h"
float * copyalloc_kernel_gpu(float * kernel_host,
......@@ -187,7 +184,6 @@ int writeFloatsToFile(float * data, // allocated array
const char * path) // file path
{
// std::ifstream input(path, std::ios::binary );
std::ofstream ofile(path, std::ios::binary);
ofile.write((char *) data, size * sizeof(float));
return 0;
......@@ -298,8 +294,6 @@ int main(int argc, char **argv)
const char* correction_vector_file = "/data_ssd/git/tile_processor_gpu/clt/main.correction_vector";
const char* geometry_correction_file = "/data_ssd/git/tile_processor_gpu/clt/main.geometry_correction";
// not yet used
/// float lpf_sigmas[3] = {0.9f, 0.9f, 0.9f}; // G, B, G
float port_offsets[NUM_CAMS][2] = {// used only in textures to scale differences
{-0.5, -0.5},
......@@ -313,7 +307,6 @@ int main(int argc, char **argv)
int KERN_TILES = KERNELS_HOR * KERNELS_VERT * NUM_COLORS;
int KERN_SIZE = KERN_TILES * 4 * 64;
// int CORR_SIZE = (2 * DTT_SIZE -1) * (2 * DTT_SIZE -1);
int CORR_SIZE = (2 * CORR_OUT_RAD + 1) * (2 * CORR_OUT_RAD + 1);
......@@ -324,7 +317,6 @@ int main(int argc, char **argv)
static struct tp_task task_data1 [TILESX*TILESY]; // maximal length - each tile
trot_deriv rot_deriv;
int corr_indices [NUM_PAIRS*TILESX*TILESY];
// int texture_indices [TILESX*TILESY];
int texture_indices [TILESX*TILESYA];
int cpu_woi [4];
......@@ -334,11 +326,14 @@ int main(int argc, char **argv)
float * gpu_images_h [NUM_CAMS];
float tile_coords_h [NUM_CAMS][TILESX * TILESY][2];
float * gpu_clt_h [NUM_CAMS];
/// float * gpu_lpf_h [NUM_COLORS]; // never used
float * gpu_corr_images_h [NUM_CAMS];
float * gpu_corrs;
int * gpu_corr_indices;
float * gpu_corrs; // correlation tiles (per tile, per pair) in pixel domain
float * gpu_corrs_td; // correlation tiles (per tile, per pair) in transform domain
int * gpu_corr_indices; // shared by gpu_corrs gpu_corrs_td
float * gpu_corrs_combo; // correlation tiles combined (1 per tile), pixel domain
float * gpu_corrs_combo_td; // correlation tiles combined (1 per tile), transform domain
int * gpu_corrs_combo_indices; // shared by gpu_corrs_combo and gpu_corrs_combo_td
float * gpu_textures;
float * gpu_diff_rgb_combo;
......@@ -358,10 +353,8 @@ int main(int argc, char **argv)
float ** gpu_images; // [NUM_CAMS];
float ** gpu_clt; // [NUM_CAMS];
float ** gpu_corr_images; // [NUM_CAMS];
/// float ** gpu_lpf; // [NUM_CAMS]; // never referenced
// GPU pointers to GPU memory
// float * gpu_tasks;
struct tp_task * gpu_tasks;
int * gpu_active_tiles;
int * gpu_num_active;
......@@ -371,9 +364,14 @@ int main(int argc, char **argv)
checkCudaErrors (cudaMalloc((void **)&gpu_num_active, sizeof(int)));
checkCudaErrors (cudaMalloc((void **)&gpu_num_corr_tiles, sizeof(int)));
size_t dstride; // in bytes !
size_t dstride_rslt; // in bytes !
size_t dstride_corr; // in bytes ! for one 2d phase correlation (padded 15x15x4 bytes)
size_t dstride; // in bytes !
size_t dstride_rslt; // in bytes !
size_t dstride_corr; // in bytes ! for one 2d phase correlation (padded 15x15x4 bytes)
// in the future, dstride_corr can reuse that of dstride_corr_td?
size_t dstride_corr_td; // in bytes ! for one 2d phase correlation (padded 4x8x8x4 bytes)
size_t dstride_corr_combo; // in bytes ! for one 2d phase correlation (padded 15x15x4 bytes)
size_t dstride_corr_combo_td; // in bytes ! for one 2d phase correlation (padded 4x8x8x4 bytes)
size_t dstride_textures; // in bytes ! for one rgba/ya 16x16 tile
size_t dstride_textures_rbga; // in bytes ! for one rgba/ya 16x16 tile
......@@ -412,20 +410,7 @@ int main(int argc, char **argv)
rByRDist_length);
checkCudaErrors(cudaMalloc((void **)&gpu_rot_deriv, sizeof(trot_deriv)));
/*
float lpf_rbg[3][64]; // not used
for (int ncol = 0; ncol < 3; ncol++) {
if (lpf_sigmas[ncol] > 0.0) {
set_clt_lpf (
lpf_rbg[ncol], // float * lpf, // size*size array to be filled out
lpf_sigmas[ncol], // float sigma,
8); // int dct_size)
gpu_lpf_h[ncol] = copyalloc_kernel_gpu(lpf_rbg[ncol], 64);
} else {
gpu_lpf_h[ncol] = NULL;
}
}
*/
for (int ncam = 0; ncam < NUM_CAMS; ncam++) {
readFloatsFromFile(
host_kern_buf, // float * data, // allocated array
......@@ -456,6 +441,24 @@ int main(int argc, char **argv)
CORR_SIZE, // int width,
NUM_PAIRS * TILESX * TILESY); // int height);
// read channel images (assuming host_kern_buf size > image size, reusing it)
// allocate all other correlation data, some may be
gpu_corrs_td = alloc_image_gpu(
&dstride_corr_td, // in bytes ! for one 2d phase correlation (padded 15x15x4 bytes)
4 * DTT_SIZE * DTT_SIZE, // int width,
NUM_PAIRS * TILESX * TILESY); // int height);
gpu_corrs_combo = alloc_image_gpu(
&dstride_corr_combo, // in bytes ! for one 2d phase correlation (padded 15x15x4 bytes)
CORR_SIZE, // int width,
TILESX * TILESY); // int height);
gpu_corrs_combo = alloc_image_gpu(
&dstride_corr_combo_td, // in bytes ! for one 2d phase correlation (padded 15x15x4 bytes)
4 * DTT_SIZE * DTT_SIZE, // int width,
TILESX * TILESY); // int height);
for (int ncam = 0; ncam < NUM_CAMS; ncam++) {
readFloatsFromFile(
host_kern_buf, // float * data, // allocated array
......@@ -539,7 +542,6 @@ int main(int argc, char **argv)
for (int ty = 0; ty < TILESY; ty++){
for (int tx = 0; tx < TILESX; tx++){
int nt = ty * TILESX + tx;
// int cm = (task_data[nt].task >> TASK_TEXTURE_BIT) & 1;
int cm = task_data[nt].task & TASK_TEXTURE_BITS;
if (cm){
texture_indices[num_textures++] = (nt << CORR_NTILE_SHIFT) | (1 << LIST_TEXTURE_BIT);
......@@ -548,7 +550,6 @@ int main(int argc, char **argv)
}
// num_textures now has the total number of textures
// copy corr_indices to gpu
// gpu_texture_indices = (int *) copyalloc_kernel_gpu((float * ) texture_indices, num_textures);
gpu_texture_indices = (int *) copyalloc_kernel_gpu(
(float * ) texture_indices,
num_textures,
......@@ -560,9 +561,9 @@ int main(int argc, char **argv)
// copy port indices to gpu
float color_weights [] = {
0.294118, // float weight0, // scale for R
0.117647, // float weight1, // scale for B
0.588235}; // float weight2, // scale for G
0.294118, // float weight0, // scale for R 0.5 / (1.0 + 0.5 +0.2)
0.117647, // float weight1, // scale for B 0.2 / (1.0 + 0.5 +0.2)
0.588235}; // float weight2, // scale for G 1.0 / (1.0 + 0.5 +0.2)
float generate_RBGA_params[]={
10.0, // float min_shot, // 10.0
3.0, // float scale_shot, // 3.0
......@@ -575,13 +576,6 @@ int main(int argc, char **argv)
gpu_color_weights = (float *) copyalloc_kernel_gpu((float * ) color_weights, sizeof(color_weights));
gpu_generate_RBGA_params = (float *) copyalloc_kernel_gpu((float * ) generate_RBGA_params, sizeof(generate_RBGA_params));
// int keep_texture_weights = 1; // try with 0 also
// int texture_colors = 3; // result will be 3+1 RGBA (for mono - 2)
// double [][] rgba = new double[numcol + 1 + (keep_weights?(ports + numcol + 1):0)][];
int tile_texture_size = (texture_colors + 1 + (keep_texture_weights? (NUM_CAMS + texture_colors + 1): 0)) *256;
gpu_textures = alloc_image_gpu(
......@@ -597,11 +591,9 @@ int main(int argc, char **argv)
&dstride_textures_rbga, // in bytes ! for one rgba/ya 16x16 tile
rgba_width, // int width (floats),
rgba_height * rbga_slices); // int height);
// checkCudaErrors(cudaMalloc((void **)&gpu_diff_rgb_combo, TILESX * TILESY * NUM_CAMS * (NUM_COLS+1)* sizeof(float)));
checkCudaErrors(cudaMalloc((void **)&gpu_diff_rgb_combo, TILESX * TILESY * NUM_CAMS * (NUM_COLORS + 1) * sizeof(float)));
// Now copy arrays of per-camera pointers to GPU memory to GPU itself
gpu_kernels = copyalloc_pointers_gpu (gpu_kernels_h, NUM_CAMS);
gpu_kernel_offsets = (struct CltExtra **) copyalloc_pointers_gpu ((float **) gpu_kernel_offsets_h, NUM_CAMS);
gpu_images = copyalloc_pointers_gpu (gpu_images_h, NUM_CAMS);
......@@ -620,8 +612,6 @@ int main(int argc, char **argv)
#define TEST_ROT_MATRICES
#ifdef TEST_ROT_MATRICES
// dim3 threads_rot(3,3,NUM_CAMS);
// dim3 grid_rot (1, 1, 1);
dim3 threads_rot(3,3,3);
dim3 grid_rot (NUM_CAMS, 1, 1);
......@@ -657,36 +647,6 @@ int main(int argc, char **argv)
gpu_rot_deriv,
sizeof(trot_deriv),
cudaMemcpyDeviceToHost));
#if 0
const char* matrices_names[] = {
"rot","d_daz","d_tilt","d_roll","d_zoom"};
for (int i = 0; i < 5;i++){
printf("Matrix %s for camera\n",matrices_names[i]);
for (int row = 0; row<3; row++){
for (int ncam = 0; ncam<NUM_CAMS;ncam++){
for (int col = 0; col <3; col++){
#ifdef NVRTC_BUG
//abuse - exceeding first dimension
printf("%9.6f,",rot_deriv.rots[i*NUM_CAMS+ncam][row][col]);
#else
printf("%9.6f,",rot_deriv.matrices[i][ncam][row][col]);
#endif
if (col == 2){
if (ncam == (NUM_CAMS-1)){
printf("\n");
} else {
printf(" ");
}
} else {
printf(" ");
}
}
}
}
}
#endif //#if 0
#endif // TEST_ROT_MATRICES
......@@ -789,10 +749,6 @@ int main(int argc, char **argv)
sdkDeleteTimer(&timerGEOM);
printf("Average TextureList run time =%f ms\n", avgTimeGEOM);
// gpu_tasks = (struct tp_task *) copyalloc_kernel_gpu((float * ) &task_data, tp_task_size * (sizeof(struct tp_task)/sizeof(float)));
// static struct tp_task task_data1 [TILESX*TILESY]; // maximal length - each tile
/// DBG_TILE
checkCudaErrors(cudaMemcpy( // copy modified/calculated tasks
&task_data1,
gpu_tasks,
......@@ -824,9 +780,6 @@ int main(int argc, char **argv)
#endif // TEST_GEOM_CORR
//create and start CUDA timer
StopWatchInterface *timerTP = 0;
sdkCreateTimer(&timerTP);
......@@ -841,10 +794,6 @@ int main(int argc, char **argv)
printf("threads_tp=(%d, %d, %d)\n",threads_tp.x,threads_tp.y,threads_tp.z);
printf("grid_tp= (%d, %d, %d)\n",grid_tp.x, grid_tp.y, grid_tp.z);
// cudaFuncSetCacheConfig(convert_correct_tiles, cudaFuncCachePreferShared);
// cudaFuncSetCacheConfig(convert_correct_tiles, cudaFuncCachePreferShared);
/// cudaProfilerStart();
float ** fgpu_kernel_offsets = (float **) gpu_kernel_offsets; // [NUM_CAMS];
......@@ -878,7 +827,6 @@ int main(int argc, char **argv)
checkCudaErrors(cudaDeviceSynchronize());
printf("%d\n",i);
}
// checkCudaErrors(cudaDeviceSynchronize());
sdkStopTimer(&timerTP);
float avgTime = (float)sdkGetTimerValue(&timerTP) / (float)numIterations;
sdkDeleteTimer(&timerTP);
......@@ -927,10 +875,6 @@ int main(int argc, char **argv)
}
#endif
// testing imclt
// dim3 threads_imclt(IMCLT_THREADS_PER_TILE, IMCLT_TILES_PER_BLOCK, 1);
// printf("threads_imclt=(%d, %d, %d)\n",threads_imclt.x,threads_imclt.y,threads_imclt.z);
StopWatchInterface *timerIMCLT = 0;
sdkCreateTimer(&timerIMCLT);
......@@ -993,10 +937,7 @@ int main(int argc, char **argv)
#ifndef NOCORR
// cudaProfilerStart();
// testing corr
// dim3 threads_corr(CORR_THREADS_PER_TILE, CORR_TILES_PER_BLOCK, 1);
// dim3 grid_corr((num_corrs + CORR_TILES_PER_BLOCK-1) / CORR_TILES_PER_BLOCK,1,1);
// printf("threads_corr=(%d, %d, %d)\n",threads_corr.x,threads_corr.y,threads_corr.z);
// testing corr
StopWatchInterface *timerCORR = 0;
sdkCreateTimer(&timerCORR);
......@@ -1011,9 +952,9 @@ int main(int argc, char **argv)
correlate2D<<<1,1>>>(
gpu_clt, // float ** gpu_clt, // [NUM_CAMS] ->[TILESY][TILESX][NUM_COLORS][DTT_SIZE*DTT_SIZE]
3, // int colors, // number of colors (3/1)
0.25, // float scale0, // scale for R
0.25, // float scale1, // scale for B
0.5, // float scale2, // scale for G
color_weights[0], // 0.25, // float scale0, // scale for R
color_weights[1], // 0.25, // float scale1, // scale for B
color_weights[2], // 0.5, // float scale2, // scale for G
30.0, // float fat_zero, // here - absolute
gpu_tasks, // struct tp_task * gpu_tasks,
tp_task_size, // int num_tiles) // number of tiles in task
......@@ -1092,8 +1033,6 @@ int main(int argc, char **argv)
textures_nonoverlap<<<1,1>>> (
gpu_tasks, // struct tp_task * gpu_tasks,
tp_task_size, // int num_tiles, // number of tiles in task list
// TILESX, // int num_tilesx, // number of tiles in a row
// declare arrays in device code?
gpu_texture_indices, // int * gpu_texture_indices,// packed tile + bits (now only (1 << 7)
gpu_num_texture_tiles, // int * pnum_texture_tiles, // returns total number of elements in gpu_texture_indices array
......@@ -1123,8 +1062,6 @@ int main(int argc, char **argv)
int rslt_texture_size = num_textures * tile_texture_size;
float * cpu_textures = (float *)malloc(rslt_texture_size * sizeof(float));
checkCudaErrors(cudaMemcpy2D(
cpu_textures,
tile_texture_size * sizeof(float),
......@@ -1156,92 +1093,12 @@ int main(int argc, char **argv)
printf(" ");
}
}
// int tile_texture_size = (texture_colors + 1 + (keep_texture_weights? (NUM_CAMS + texture_colors + 1): 0)) *256;
#endif // DEBUG9
#endif
free(cpu_textures);
#endif // ifndef NOTEXTURES
#undef GEN_TEXTURE_LIST
#ifdef GEN_TEXTURE_LIST
dim3 threads_list(1,1, 1); // TEXTURE_TILES_PER_BLOCK, 1);
dim3 grid_list (1,1,1);
printf("threads_list=(%d, %d, %d)\n",threads_list.x,threads_list.y,threads_list.z);
printf("grid_list=(%d, %d, %d)\n",grid_list.x,grid_list.y,grid_list.z);
StopWatchInterface *timerTEXTURELIST = 0;
sdkCreateTimer(&timerTEXTURELIST);
for (int i = i0; i < numIterations; i++)
{
if (i == 0)
{
checkCudaErrors(cudaDeviceSynchronize());
sdkResetTimer(&timerTEXTURELIST);
sdkStartTimer(&timerTEXTURELIST);
}
prepare_texture_list<<<grid_list,threads_list>>> (
gpu_tasks, // struct tp_task * gpu_tasks,
tp_task_size, // int num_tiles, // number of tiles in task list
gpu_texture_indices, // int * gpu_texture_indices,// packed tile + bits (now only (1 << 7)
gpu_num_texture_tiles, // int * num_texture_tiles, // number of texture tiles to process (8 elements)
gpu_woi, // int * woi, // x,y,width,height of the woi
TILESX, // int width, // <= TILESX, use for faster processing of LWIR images (should be actual + 1)
TILESY); // int height); // <= TILESY, use for faster processing of LWIR images
getLastCudaError("Kernel failure");
checkCudaErrors(cudaDeviceSynchronize());
printf("test pass: %d\n",i);
}
/// cudaProfilerStop();
sdkStopTimer(&timerTEXTURELIST);
float avgTimeTEXTURESLIST = (float)sdkGetTimerValue(&timerTEXTURELIST) / (float)numIterations;
sdkDeleteTimer(&timerTEXTURELIST);
printf("Average TextureList run time =%f ms\n", avgTimeTEXTURESLIST);
int cpu_num_texture_tiles[8];
checkCudaErrors(cudaMemcpy(
cpu_woi,
gpu_woi,
4 * sizeof(float),
cudaMemcpyDeviceToHost));
printf("WOI x=%d, y=%d, width=%d, height=%d\n", cpu_woi[0], cpu_woi[1], cpu_woi[2], cpu_woi[3]);
checkCudaErrors(cudaMemcpy(
cpu_num_texture_tiles,
gpu_num_texture_tiles,
8 * sizeof(float), // 8 sequences (0,2,4,6 - non-border, growing up;
//1,3,5,7 - border, growing down from the end of the corresponding non-border buffers
cudaMemcpyDeviceToHost));
printf("cpu_num_texture_tiles=(%d(%d), %d(%d), %d(%d), %d(%d) -> %d tp_task_size=%d)\n",
cpu_num_texture_tiles[0], cpu_num_texture_tiles[1],
cpu_num_texture_tiles[2], cpu_num_texture_tiles[3],
cpu_num_texture_tiles[4], cpu_num_texture_tiles[5],
cpu_num_texture_tiles[6], cpu_num_texture_tiles[7],
cpu_num_texture_tiles[0] + cpu_num_texture_tiles[1] +
cpu_num_texture_tiles[2] + cpu_num_texture_tiles[3] +
cpu_num_texture_tiles[4] + cpu_num_texture_tiles[5] +
cpu_num_texture_tiles[6] + cpu_num_texture_tiles[7],
tp_task_size
);
for (int q = 0; q < 4; q++) {
checkCudaErrors(cudaMemcpy(
texture_indices + q * TILESX * (TILESYA >> 2),
gpu_texture_indices + q * TILESX * (TILESYA >> 2),
cpu_num_texture_tiles[q] * sizeof(float), // change to cpu_num_texture_tiles when ready
cudaMemcpyDeviceToHost));
}
for (int q = 0; q < 4; q++) {
printf("%d: %3x:%3x %3x:%3x %3x:%3x %3x:%3x %3x:%3x %3x:%3x %3x:%3x %3x:%3x \n",q,
(texture_indices[q * TILESX * (TILESYA >> 2) + 0] >> 8) / TILESX, (texture_indices[q * TILESX * (TILESYA >> 2) + 0] >> 8) % TILESX,
(texture_indices[q * TILESX * (TILESYA >> 2) + 1] >> 8) / TILESX, (texture_indices[q * TILESX * (TILESYA >> 2) + 1] >> 8) % TILESX,
(texture_indices[q * TILESX * (TILESYA >> 2) + 2] >> 8) / TILESX, (texture_indices[q * TILESX * (TILESYA >> 2) + 2] >> 8) % TILESX,
(texture_indices[q * TILESX * (TILESYA >> 2) + 3] >> 8) / TILESX, (texture_indices[q * TILESX * (TILESYA >> 2) + 3] >> 8) % TILESX,
(texture_indices[q * TILESX * (TILESYA >> 2) + 4] >> 8) / TILESX, (texture_indices[q * TILESX * (TILESYA >> 2) + 4] >> 8) % TILESX,
(texture_indices[q * TILESX * (TILESYA >> 2) + 5] >> 8) / TILESX, (texture_indices[q * TILESX * (TILESYA >> 2) + 5] >> 8) % TILESX,
(texture_indices[q * TILESX * (TILESYA >> 2) + 6] >> 8) / TILESX, (texture_indices[q * TILESX * (TILESYA >> 2) + 6] >> 8) % TILESX,
(texture_indices[q * TILESX * (TILESYA >> 2) + 7] >> 8) / TILESX, (texture_indices[q * TILESX * (TILESYA >> 2) + 7] >> 8) % TILESX);
}
#endif //GEN_TEXTURE_LIST
......@@ -1278,19 +1135,11 @@ int main(int argc, char **argv)
texture_colors, // int colors, // number of colors (3/1)
(texture_colors == 1), // int is_lwir, // do not perform shot correction
gpu_generate_RBGA_params,
/*
10.0, // float min_shot, // 10.0
3.0, // float scale_shot, // 3.0
1.5f, // float diff_sigma, // pixel value/pixel change
10.0f, // float diff_threshold, // pixel value/pixel change
3.0, // float min_agree, // minimal number of channels to agree on a point (real number to work with fuzzy averages)
*/
gpu_color_weights, // float weights[3], // scale for R
1, // int dust_remove, // Do not reduce average weight when only one image differes much from the average
0, // int keep_weights, // return channel weights after A in RGBA
dstride_textures_rbga/sizeof(float), // const size_t texture_rbga_stride, // in floats
gpu_textures_rbga); // float * gpu_texture_tiles) // (number of colors +1 + ?)*16*16 rgba texture tiles
// (float *) 0 ); // gpu_diff_rgb_combo); // float * gpu_diff_rgb_combo) // diff[NUM_CAMS], R[NUM_CAMS], B[NUM_CAMS],G[NUM_CAMS]
getLastCudaError("Kernel failure");
checkCudaErrors(cudaDeviceSynchronize());
......
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