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tile_processor_gpu
Commit 6fc2c45f authored by Andrey Filippov's avatar Andrey Filippov
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Changes from May 2022

parent f72f2a9c
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Showing with 233 additions and 13 deletions
src/TileProcessor.cuh
View file @ 6fc2c45f
......@@ -437,6 +437,7 @@ __constant__ float lpf_rb_corr[64]={ // modify if needed
0.32891038f, 0.30456742f, 0.26124917f, 0.20786692f, 0.15413642f, 0.10818204f, 0.07536856f, 0.05845371f,
0.22914618f, 0.21218686f, 0.18200779f, 0.14481729f, 0.10738418f, 0.07536856f, 0.05250797f, 0.04072369f,
0.17771927f, 0.16456610f, 0.14116007f, 0.11231618f, 0.08328412f, 0.05845371f, 0.04072369f, 0.03158414f
};
__constant__ float lpf_corr[64]={ // modify if needed
1.00000000f, 0.87041007f, 0.65943687f, 0.43487258f, 0.24970076f, 0.12518080f, 0.05616371f, 0.02728573f,
......@@ -447,6 +448,7 @@ __constant__ float lpf_corr[64]={ // modify if needed
0.12518080f, 0.10895863f, 0.08254883f, 0.05443770f, 0.03125774f, 0.01567023f, 0.00703062f, 0.00341565f,
0.05616371f, 0.04888546f, 0.03703642f, 0.02442406f, 0.01402412f, 0.00703062f, 0.00315436f, 0.00153247f,
0.02728573f, 0.02374977f, 0.01799322f, 0.01186582f, 0.00681327f, 0.00341565f, 0.00153247f, 0.00074451f
};
__constant__ float LoG_corr[64]={ // modify if needed high-pass filter before correlation to fit into float range
......@@ -1389,7 +1391,6 @@ extern "C" __global__ void combine_inter( // combine per-senor interscene co
clt += DTT_SIZE1;
mem_corr += DTT_SIZE;
}
corr_offset++;
}
......@@ -1825,7 +1826,7 @@ extern "C" __global__ void correlate2D_inner(
* Combine multiple correlation pairs for quad (square) camera: 2 or 4 ortho into a single clt tile,
* and separately the two diagonals into another single one
* When adding vertical pairs to the horizontal, each quadrant is transposed, and the Q1 and Q2 are also swapped.
* when combining tho diagonals (down-right and up-right), the data in quadrants Q2 and Q3 is negated
* when combining two diagonals (down-right and up-right), the data in quadrants Q2 and Q3 is negated
* (corresponds to a vertical flip).
* Data can be added to the existing one (e.g. for the inter-scene accumulation of the compatible correlations).
* This is an outer kernel that calls the inner one with CDP, this one should be configured as corr2D_combine<<<1,1>>>
......
src/test_tp.cu
View file @ 6fc2c45f
......@@ -138,14 +138,97 @@ float ** copyalloc_pointers_gpu(float ** gpu_pointer,
return gpu_pointer_to_gpu_pointers;
}
// shift image in-place, repeat lines/columns
void shift_image (
float * image,
int width,
int height,
int bayer,
int dx,
int dy)
{
int step = 1;
if (bayer){
step = 2;
dx &= -2;
dy &= -2;
}
// vertical shift dy>0 - down, dy < 0 - up
for (int m = 0; m < dy; m+= step) { // only if dy > 0 (down)
for (int y = height - 1; y >= step; y++){
float * dp = image + (y * width);
float * sp = dp - step * width;
for (int x = 0; x < width; x++){
(*dp++) = (*sp++);
}
}
}
float * copyalloc_image_gpu(float * image_host,
size_t* dstride, // in floats !
int width,
int height)
// vertical shift dy < 0 - up
for (int m = 0; m > dy; m-= step) { // only if dy < 0 (up)
for (int y = 0; y < height - step; y++){
float * dp = image + (y * width);
float * sp = dp + step * width;
for (int x = 0; x < width; x++){
(*dp++) = (*sp++);
}
}
}
// horizontal shift dx > 0 - right, dx < 0 - left
for (int m = 0; m < dx; m+= step) { // only if dx > 0 (right)
for (int y = 0; y < height; y++){
float * dp = image + (y * width) + width - 1;
float * sp = dp - step;
for (int x = 0; x < (width - step); x++){
(*dp--) = (*sp--);
}
}
}
// horizontal shift dx < 0 - left
for (int m = 0; m > dx; m-= step) { // only if dx < 0 (left)
for (int y = 0; y < height; y++){
float * dp = image + (y * width);
float * sp = dp + step;
for (int x = 0; x < (width - step); x++){
(*dp++) = (*sp++);
}
}
}
}
void update_image_gpu(
float * image_host,
float * image_gpu,
size_t dstride, // in floats !
int width,
int height){
checkCudaErrors(cudaMemcpy2D(
image_gpu,
dstride, // * sizeof(float),
image_host,
width * sizeof(float), // make in 16*n?
width * sizeof(float),
height,
cudaMemcpyHostToDevice));
}
float * copyalloc_image_gpu(
float * image_host,
size_t* dstride, // in floats !
int width,
int height)
{
float *image_gpu;
checkCudaErrors(cudaMallocPitch((void **)&image_gpu, dstride, width * sizeof(float), height));
update_image_gpu(
image_host,
image_gpu,
*dstride, // in floats !
width,
height);
/*
checkCudaErrors(cudaMemcpy2D(
image_gpu,
*dstride, // * sizeof(float),
......@@ -154,6 +237,7 @@ float * copyalloc_image_gpu(float * image_host,
width * sizeof(float),
height,
cudaMemcpyHostToDevice));
*/
return image_gpu;
}
......@@ -569,6 +653,8 @@ int main(int argc, char **argv)
//initialize CUDA
findCudaDevice(argc, (const char **)argv);
float fat_zero = 1000.0f; // 300.0f; // 30.0;
#if TEST_LWIR
const char* kernel_file[] = {
"clt/aux_chn0_transposed.kernel",
......@@ -996,7 +1082,6 @@ int main(int argc, char **argv)
TILESX * TILESY); // int height);
// for (int ncam = 0; ncam < NUM_CAMS; ncam++) {
for (int ncam = 0; ncam < num_cams; ncam++) {
readFloatsFromFile(
host_kern_buf, // float * data, // allocated array
......@@ -1493,7 +1578,7 @@ int main(int argc, char **argv)
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 * 30.0, // float fat_zero2, // here - absolute
fat_zero * fat_zero, // float fat_zero2, // here - absolute
gpu_ftasks, // float * gpu_ftasks, // flattened tasks, 27 floats for quad EO, 99 floats for LWIR16
tp_task_size, // int num_tiles) // number of tiles in task
TILESX, // int tilesx, // number of tile rows
......@@ -1618,7 +1703,7 @@ int main(int argc, char **argv)
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*30.0, // float fat_zero2, // here - absolute (squared)
fat_zero*fat_zero, // float fat_zero2, // here - absolute (squared)
gpu_ftasks, // float * gpu_ftasks, // flattened tasks, 27 floats for quad EO, 99 floats for LWIR16
tp_task_size, // int num_tiles) // number of tiles in task
TILESX, // int tilesx, // number of tile rows
......@@ -1662,7 +1747,7 @@ int main(int argc, char **argv)
(float *) 0, // corr_weights, // float * corr_weights, // null or per-tile weight (fat_zero2 will be divided by it)
dstride_corr_combo/sizeof(float), // const size_t corr_stride, // in floats
gpu_corrs_combo, // float * gpu_corrs, // correlation output data (pixel domain)
30.0 * 30.0, // float fat_zero2, // here - absolute
fat_zero * fat_zero, // float fat_zero2, // here - absolute
CORR_OUT_RAD); // int corr_radius); // radius of the output correlation (7 for 15x15)
#else
checkCudaErrors(cudaDeviceSynchronize());
......@@ -1674,7 +1759,7 @@ int main(int argc, char **argv)
(float *) 0, // corr_weights, // float * corr_weights, // null or per-tile weight (fat_zero2 will be divided by it)
dstride_corr/sizeof(float), // const size_t corr_stride, // in floats
gpu_corrs, // float * gpu_corrs, // correlation output data (pixel domain)
30.0 * 30.0, // float fat_zero2, // here - absolute
fat_zero * fat_zero, // float fat_zero2, // here - absolute
CORR_OUT_RAD); // int corr_radius); // radius of the output correlation (7 for 15x15)
#endif
getLastCudaError("Kernel failure:corr2D_normalize");
......@@ -1785,6 +1870,54 @@ int main(int argc, char **argv)
corr_img_size, // int size, // length in elements
result_corr_td_norm_file); // const char * path) // file path
#endif
#if 1 // export TD intra
int intra_corr_size_td = num_corrs * DTT_SIZE2*DTT_SIZE2;
cpu_corr_td = (float *)malloc(intra_corr_size_td * sizeof(float));
checkCudaErrors(cudaMemcpy2D(
cpu_corr_td,
(DTT_SIZE2*DTT_SIZE2) * sizeof(float),
gpu_corrs_td,
dstride_corr_td,
(DTT_SIZE2*DTT_SIZE2) * sizeof(float),
num_corrs,
cudaMemcpyDeviceToHost));
// Reuse the same corr_img for TD images - each tile is still 16x16 (corr was 15x15 and gap)
for (int ict = 0; ict < num_corr_indices; ict++){
int ctt = ( cpu_corr_indices[ict] >> CORR_NTILE_SHIFT);
int cpair = cpu_corr_indices[ict] & ((1 << CORR_NTILE_SHIFT) - 1);
int ty = ctt / TILESX;
int tx = ctt % TILESX;
int src_offs0 = ict * DTT_SIZE2*DTT_SIZE2;
int dst_offs0 = cpair * (num_tiles * 16 * 16) + (ty * 16 * TILESX * 16) + (tx * 16);
for (int iquad = 0; iquad < 4; iquad ++) {
int iqy = (iquad >> 1) & 1;
int iqx = (iquad >> 0) & 1;
for (int iy = 0; iy < DTT_SIZE; iy++){
int src_offs = src_offs0 + iy * DTT_SIZE + iquad * DTT_SIZE * DTT_SIZE;
int dst_offs = dst_offs0 + (iy + DTT_SIZE * iqy)* (TILESX * 16) + iqx * DTT_SIZE;
for (int ix = 0; ix < DTT_SIZE; ix++){
corr_img[dst_offs++] = cpu_corr_td[src_offs++];
}
}
}
}
#ifndef NSAVE_CORR
printf("Writing intrascene phase correlation TD data");
writeFloatsToFile(
corr_img, // float * data, // allocated array
corr_img_size, // int size, // length in elements
"clt/aux_intrascene-TD.raw"); // const char * path) // file path
#endif
free (cpu_corr_td);
#endif // if 1
// reuse image, export TD data
free (cpu_corr);
free (cpu_corr_indices);
free (corr_img);
......@@ -1793,6 +1926,8 @@ int main(int argc, char **argv)
#endif // ifndef NOCORR_TD
// Testing "interframe" correlation with itself, assuming direct convert already ran
......@@ -1803,6 +1938,84 @@ int main(int argc, char **argv)
int num_sel_sensors = 16; // 15; // 16;
num_pairs = num_sel_sensors+1;
num_corr_indices = num_pairs * num_tiles;
int is_bayer = 0;
int image_dx = 2;
int image_dy = 0;
float * gpu_clt_ref_h [num_cams];
float ** gpu_clt_ref; // [NUM_CAMS];
for (int ncam = 0; ncam < num_cams; ncam++) {
gpu_clt_ref_h[ncam] = alloc_kernel_gpu(TILESY * TILESX * num_colors * 4 * DTT_SIZE * DTT_SIZE);
}
gpu_clt_ref = copyalloc_pointers_gpu (gpu_clt_ref_h, num_cams); // NUM_CAMS);
// use gpu_images and convert to gpu_clt_ref
convert_direct<<<grid_tp,threads_tp>>>( // called with a single block, CONVERT_DIRECT_INDEXING_THREADS threads
num_cams, // int num_cams, // actual number of cameras
num_colors, // int num_colors, // actual number of colors: 3 for RGB, 1 for LWIR/mono
fgpu_kernel_offsets, // struct CltExtra ** gpu_kernel_offsets,
gpu_kernels, // float ** gpu_kernels,
gpu_images, // float ** gpu_images,
gpu_ftasks, // float * gpu_ftasks, // flattened tasks, 27 floats for quad EO, 99 floats for LWIR16
gpu_clt_ref, //****** // float ** gpu_clt, // [num_cams][TILESY][TILESX][num_colors][DTT_SIZE*DTT_SIZE]
dstride/sizeof(float), // size_t dstride, // for gpu_images
tp_task_size, // int num_tiles) // number of tiles in task
0, // int lpf_mask) // apply lpf to colors : bit 0 - red, bit 1 - blue, bit2 - green
IMG_WIDTH, // int woi_width,
IMG_HEIGHT, // int woi_height,
KERNELS_HOR, // int kernels_hor,
KERNELS_VERT, // int kernels_vert);
gpu_active_tiles, // int * gpu_active_tiles, // pointer to the calculated number of non-zero tiles
gpu_num_active, //); // int * pnum_active_tiles); // indices to gpu_tasks
TILESX); // int tilesx)
getLastCudaError("Kernel execution failed");
checkCudaErrors(cudaDeviceSynchronize());
// re-read same images. shift them, update gpu_images and convert to gpu_clt;
for (int ncam = 0; ncam < num_cams; ncam++) {
readFloatsFromFile(
host_kern_buf, // float * data, // allocated array
image_files[ncam]); // char * path) // file path
shift_image (
host_kern_buf, // float * image,
IMG_WIDTH, // int width,
IMG_HEIGHT, // int height,
is_bayer, // int bayer,
image_dx, // int dx,
image_dy); // int dy);
update_image_gpu(
host_kern_buf, // float * image_host,
gpu_images_h[ncam], // float * image_gpu,
dstride, // size_t dstride, // in floats !
IMG_WIDTH, // int width,
IMG_HEIGHT); // int height);
}
convert_direct<<<grid_tp,threads_tp>>>( // called with a single block, CONVERT_DIRECT_INDEXING_THREADS threads
num_cams, // int num_cams, // actual number of cameras
num_colors, // int num_colors, // actual number of colors: 3 for RGB, 1 for LWIR/mono
fgpu_kernel_offsets, // struct CltExtra ** gpu_kernel_offsets,
gpu_kernels, // float ** gpu_kernels,
gpu_images, // float ** gpu_images,
gpu_ftasks, // float * gpu_ftasks, // flattened tasks, 27 floats for quad EO, 99 floats for LWIR16
gpu_clt, //****** // float ** gpu_clt, // [num_cams][TILESY][TILESX][num_colors][DTT_SIZE*DTT_SIZE]
dstride/sizeof(float), // size_t dstride, // for gpu_images
tp_task_size, // int num_tiles) // number of tiles in task
0, // int lpf_mask) // apply lpf to colors : bit 0 - red, bit 1 - blue, bit2 - green
IMG_WIDTH, // int woi_width,
IMG_HEIGHT, // int woi_height,
KERNELS_HOR, // int kernels_hor,
KERNELS_VERT, // int kernels_vert);
gpu_active_tiles, // int * gpu_active_tiles, // pointer to the calculated number of non-zero tiles
gpu_num_active, //); // int * pnum_active_tiles); // indices to gpu_tasks
TILESX); // int tilesx)
getLastCudaError("Kernel execution failed");
checkCudaErrors(cudaDeviceSynchronize());
StopWatchInterface *timerINTERSELF = 0;
sdkCreateTimer(&timerINTERSELF);
// int num_corr_combo_inter;
......@@ -1818,7 +2031,7 @@ int main(int argc, char **argv)
num_cams, // int num_cams,
sel_sensors, // int sel_sensors,
gpu_clt, // float ** gpu_clt, // [num_cams] ->[TILES-Y][TILES-X][colors][DTT_SIZE*DTT_SIZE]
gpu_clt, // float ** gpu_clt_ref, // [num_cams] ->[TILES-Y][TILES-X][colors][DTT_SIZE*DTT_SIZE]
gpu_clt_ref, // ********* // float ** gpu_clt_ref, // [num_cams] ->[TILES-Y][TILES-X][colors][DTT_SIZE*DTT_SIZE]
num_colors, // int colors, // number of colors (3/1)
color_weights[0], // 0.25, // float scale0, // scale for R
color_weights[1], // 0.25, // float scale1, // scale for B
......@@ -1846,7 +2059,7 @@ int main(int argc, char **argv)
(float *) 0, // corr_weights, // float * corr_weights, // null or per-tile weight (fat_zero2 will be divided by it)
dstride_corr/sizeof(float), // const size_t corr_stride, // in floats
gpu_corrs, // float * gpu_corrs, // correlation output data (pixel domain)
30.0 * 30.0, // float fat_zero2, // here - absolute
fat_zero * fat_zero, // float fat_zero2, // here - absolute
CORR_OUT_RAD); // int corr_radius); // radius of the output correlation (7 for 15x15)
getLastCudaError("Kernel failure:corr2D_normalize");
checkCudaErrors(cudaDeviceSynchronize());
......@@ -1989,6 +2202,12 @@ int main(int argc, char **argv)
free (cpu_corr);
free (cpu_corr_indices);
free (corr_img);
for (int ncam = 0; ncam < num_cams; ncam++){
checkCudaErrors(cudaFree(gpu_clt_ref_h[ncam]));
}
checkCudaErrors(cudaFree(gpu_clt_ref));
#endif // #ifdef CORR_INTER_SELF
......
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