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imagej-elphel
Commit 907cda8d authored by Andrey Filippov's avatar Andrey Filippov
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Using Marco's help to make jcuda work with nvrtc with cdp

parent 0d087c0b
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src/main/java/com/elphel/imagej/cameras/CLTParameters.java
View file @ 907cda8d
......@@ -333,7 +333,7 @@ public class CLTParameters {
public double infinityDistance = 10000; // Distance to generate backdrop (0 - use regular backdrop)
public int min_bgnd_tiles = 10; // Minimal number of background tiles to generate background
public boolean shUseFlaps = true; // Split into shells with flaps
public boolean shAggrFade = true; // Aggressive fade alpha (whole boundary)
public boolean shAggrFade = false; // true; // Aggressive fade alpha (whole boundary)
public int shMinArea = 1; // Minimal shell area (not counting flaps
public double shMinStrength = 0.2; // Minimal value of the shell maximum strength
......
src/main/java/com/elphel/imagej/gpu/GPUTileProcessor.java
View file @ 907cda8d
......@@ -26,19 +26,29 @@ package com.elphel.imagej.gpu;
**
*/
import static jcuda.driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR;
import static jcuda.driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR;
// Uses code by Marco Hutter - http://www.jcuda.org
import static jcuda.driver.CUjitInputType.CU_JIT_INPUT_LIBRARY;
import static jcuda.driver.CUjitInputType.CU_JIT_INPUT_PTX;
import static jcuda.driver.JCudaDriver.cuCtxCreate;
import static jcuda.driver.JCudaDriver.cuCtxSynchronize;
import static jcuda.driver.JCudaDriver.cuDeviceGet;
import static jcuda.driver.JCudaDriver.cuDeviceGetAttribute;
import static jcuda.driver.JCudaDriver.cuInit;
import static jcuda.driver.JCudaDriver.cuLaunchKernel;
import static jcuda.driver.JCudaDriver.cuLinkAddData;
import static jcuda.driver.JCudaDriver.cuLinkAddFile;
import static jcuda.driver.JCudaDriver.cuLinkComplete;
import static jcuda.driver.JCudaDriver.cuLinkCreate;
import static jcuda.driver.JCudaDriver.cuLinkDestroy;
import static jcuda.driver.JCudaDriver.cuMemAlloc;
import static jcuda.driver.JCudaDriver.cuMemAllocPitch;
import static jcuda.driver.JCudaDriver.cuMemcpy2D;
import static jcuda.driver.JCudaDriver.cuMemcpyHtoD;
import static jcuda.driver.JCudaDriver.cuModuleGetFunction;
import static jcuda.driver.JCudaDriver.cuModuleGetGlobal;
import static jcuda.driver.JCudaDriver.cuModuleLoadData;
import static jcuda.driver.JCudaDriver.cuModuleLoadDataEx;
import static jcuda.nvrtc.JNvrtc.nvrtcCompileProgram;
import static jcuda.nvrtc.JNvrtc.nvrtcCreateProgram;
import static jcuda.nvrtc.JNvrtc.nvrtcDestroyProgram;
......@@ -66,14 +76,17 @@ import jcuda.driver.CUcontext;
import jcuda.driver.CUdevice;
import jcuda.driver.CUdeviceptr;
import jcuda.driver.CUfunction;
import jcuda.driver.CUlinkState;
import jcuda.driver.CUmemorytype;
import jcuda.driver.CUmodule;
import jcuda.driver.JCudaDriver;
import jcuda.driver.JITOptions;
import jcuda.nvrtc.JNvrtc;
import jcuda.nvrtc.nvrtcProgram;
public class GPUTileProcessor {
static String GPU_KERNEL_FILE = "dtt8x8.cuh";
String LIBRARY_PATH = "/usr/local/cuda/targets/x86_64-linux/lib/libcudadevrt.a"; // linux
static String GPU_RESOURCE_DIR = "kernels";
static String [] GPU_KERNEL_FILES = {"dtt8x8.cuh","TileProcessor.cuh"};
static String GPU_CONVERT_CORRECT_TILES_NAME = "convert_correct_tiles"; // name in C code
static String GPU_IMCLT_RBG_NAME = "imclt_rbg"; // name in C code
......@@ -112,6 +125,7 @@ public class GPUTileProcessor {
public static int CORR_OUT_RAD = 4; // output radius of the correlations (implemented)
public static double FAT_ZERO_WEIGHT = 0.0001; // add to port weights to avoid nan
public static int THREADS_DYNAMIC_BITS = 5; // treads in block for CDP creation of the texture list
int DTTTEST_BLOCK_WIDTH = 32; // may be read from the source code
int DTTTEST_BLOCK_HEIGHT = 16; // may be read from the source code
......@@ -129,7 +143,6 @@ public class GPUTileProcessor {
private CUdeviceptr [] gpu_kernel_offsets_h = new CUdeviceptr[NUM_CAMS];
private CUdeviceptr [] gpu_bayer_h = new CUdeviceptr[NUM_CAMS];
private CUdeviceptr [] gpu_clt_h = new CUdeviceptr[NUM_CAMS];
// private CUdeviceptr [] gpu_lpf_h = new CUdeviceptr[NUM_COLORS];
private CUdeviceptr [] gpu_corr_images_h= new CUdeviceptr[NUM_CAMS];
// GPU pointers to array of GPU pointers
......@@ -143,9 +156,7 @@ public class GPUTileProcessor {
private CUdeviceptr gpu_corr_indices = new CUdeviceptr(); // allocate tilesX * tilesY * 6 * Sizeof.POINTER
private CUdeviceptr gpu_texture_indices = new CUdeviceptr(); // allocate tilesX * tilesY * 6 * Sizeof.POINTER
private CUdeviceptr gpu_port_offsets = new CUdeviceptr(); // allocate Quad * 2 * Sizeof.POINTER
// private
CUmodule module; // to access constants memory
// private CUdeviceptr gpu_lpf = new CUdeviceptr();
private int mclt_stride;
private int corr_stride;
private int imclt_stride;
......@@ -153,7 +164,6 @@ public class GPUTileProcessor {
public int num_task_tiles;
public int num_corr_tiles;
public int num_texture_tiles;
public class TpTask {
public int task; // [0](+1) - generate 4 images, [4..9]+16..+512 - correlation pairs, 2 - generate texture tiles
public float target_disparity;
......@@ -267,6 +277,7 @@ public class GPUTileProcessor {
public GPUTileProcessor(String cuda_project_directory) throws IOException
{
// From code by Marco Hutter - http://www.jcuda.org
// Enable exceptions and omit all subsequent error checks
JCudaDriver.setExceptionsEnabled(true);
......@@ -274,13 +285,24 @@ public class GPUTileProcessor {
// Initialize the driver and create a context for the first device.
cuInit(0);
CUdevice device = new CUdevice();
//2020 - making them global
CUdevice
device = new CUdevice();
cuDeviceGet(device, 0);
CUcontext context = new CUcontext();
CUcontext
context = new CUcontext();
cuCtxCreate(context, 0, device);
int majorArray[] = { 0 };
int minorArray[] = { 0 };
cuDeviceGetAttribute(majorArray, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, device);
cuDeviceGetAttribute(minorArray, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, device);
int major = majorArray[0];
int minor = minorArray[0];
int capability = major * 10 + minor;
// Obtain the CUDA source code from the CUDA file
// Get absolute path to the file in resource foldder, then read it as a normal file.
// Get absolute path to the file in resource folder, then read it as a normal file.
// When using just Eclipse resources - it does not notice that the file
// was edited (happens frequently during kernel development).
ClassLoader classLoader = getClass().getClassLoader();
......@@ -311,12 +333,14 @@ public class GPUTileProcessor {
"#define TASK_TEXTURE_BIT " + TASK_TEXTURE_BIT+"\n"+
"#define LIST_TEXTURE_BIT " + LIST_TEXTURE_BIT+"\n"+
"#define CORR_OUT_RAD " + CORR_OUT_RAD+"\n" +
"#define FAT_ZERO_WEIGHT " + FAT_ZERO_WEIGHT+"\n";
"#define FAT_ZERO_WEIGHT " + FAT_ZERO_WEIGHT+"\n"+
"#define THREADS_DYNAMIC_BITS " + THREADS_DYNAMIC_BITS+"\n";
for (String src_file:GPU_KERNEL_FILES) {
File file = null;
if ((cuda_project_directory == null) || (cuda_project_directory == "")) {
file = new File(classLoader.getResource(src_file).getFile());
if ((cuda_project_directory == null) || cuda_project_directory.isEmpty()) {
file = new File(classLoader.getResource(GPU_RESOURCE_DIR+"/"+src_file).getFile());
System.out.println("Loading resource "+file);
} else {
File src_dir = new File(cuda_project_directory, "src");
......@@ -336,11 +360,15 @@ public class GPUTileProcessor {
}
// Create the kernel functions (first - just test)
String [] func_names = {GPU_CONVERT_CORRECT_TILES_NAME, GPU_IMCLT_RBG_NAME, GPU_CORRELATE2D_NAME, GPU_TEXTURES_NAME};
CUfunction[] functions = createFunctions(kernelSource, func_names);
CUfunction[] functions = createFunctions(kernelSource,
func_names,
capability); // on my - 75
this.GPU_CONVERT_CORRECT_TILES_kernel = functions[0];
this.GPU_IMCLT_RBG_kernel = functions[1];
this.GPU_CORRELATE2D_kernel = functions[2];
this.GPU_TEXTURES_kernel= functions[3];
System.out.println("GPU kernel functions initialized");
System.out.println(GPU_CONVERT_CORRECT_TILES_kernel.toString());
System.out.println(GPU_IMCLT_RBG_kernel.toString());
......@@ -968,11 +996,12 @@ public class GPUTileProcessor {
int num_colors,
boolean keep_weights){
int texture_slices = (num_colors + 1 + (keep_weights?(NUM_CAMS + num_colors + 1):0));
int texture_slice_size = (2 * DTT_SIZE)* (2 * DTT_SIZE);
int texture_tile_size = texture_slices * texture_slice_size;
int texture_size = texture_tile_size * num_texture_tiles;
float [] cpu_textures = new float [ num_texture_tiles * texture_size];
int texture_slices = (num_colors + 1 + (keep_weights?(NUM_CAMS + num_colors + 1):0)); // number of texture slices
int texture_slice_size = (2 * DTT_SIZE)* (2 * DTT_SIZE); // number of (float) elements in a single slice of a tile
int texture_tile_size = texture_slices * texture_slice_size; // number of (float) elements in a multi-slice tile
int texture_size = texture_tile_size * num_texture_tiles; // number of (float) elements in the whole texture
// float [] cpu_textures = new float [ num_texture_tiles * texture_size];
float [] cpu_textures = new float [texture_size];
CUDA_MEMCPY2D copyD2H = new CUDA_MEMCPY2D();
copyD2H.srcMemoryType = CUmemorytype.CU_MEMORYTYPE_DEVICE;
copyD2H.srcDevice = gpu_textures;
......@@ -1104,51 +1133,62 @@ public class GPUTileProcessor {
}
// private static CUfunction [] createFunctions(
private CUfunction [] createFunctions(
String sourceCode, String [] kernelNames) throws IOException
{
private CUfunction [] createFunctions(
String sourceCode,
String [] kernelNames,
int capability
) throws IOException
{
CUfunction [] functions = new CUfunction [kernelNames.length];
boolean OK = false;
// Use the NVRTC to create a program by compiling the source code
nvrtcProgram program = new nvrtcProgram();
nvrtcCreateProgram(
program, sourceCode, null, 0, null, null);
try {
nvrtcCompileProgram(program, 0, null);
OK = true;
} catch (Exception e) {
System.out.println("nvrtcCompileProgram() FAILED");
}
// Compilation log with errors/warnongs
String programLog[] = new String[1];
nvrtcGetProgramLog(program, programLog);
String log = programLog[0].trim();
if (!log.isEmpty())
{
System.err.println("Program compilation log:\n" + log);
}
if (!OK) {
throw new IOException("Could not compile program");
}
// Get the PTX code of the compiled program (not the binary)
String[] ptx = new String[1];
nvrtcGetPTX(program, ptx);
nvrtcDestroyProgram(program);
boolean OK = false;
// Use the NVRTC to create a program by compiling the source code
nvrtcProgram program = new nvrtcProgram();
nvrtcCreateProgram( program, sourceCode, null, 0, null, null);
String options[] = {"--gpu-architecture=compute_"+capability};
// Create a CUDA module from the PTX code
// CUmodule
module = new CUmodule();
cuModuleLoadData(module, ptx[0]);
try {
nvrtcCompileProgram(program, options.length, options);
OK = true;
} catch (Exception e) {
System.out.println("nvrtcCompileProgram() FAILED");
}
// Compilation log with errors/warnings
String programLog[] = new String[1];
nvrtcGetProgramLog(program, programLog);
String log = programLog[0].trim();
if (!log.isEmpty())
{
System.err.println("Program compilation log:\n" + log);
}
if (!OK) {
throw new IOException("Could not compile program");
}
for (int i = 0; i < kernelNames.length; i++) {
// Find the function in the source by name, get its pointer
functions[i] = new CUfunction();
cuModuleGetFunction(functions[i] , module, kernelNames[i]);
}
// Get the PTX code of the compiled program (not the binary)
String[] ptx = new String[1];
nvrtcGetPTX(program, ptx);
nvrtcDestroyProgram(program);
byte[] ptxData = ptx[0].getBytes();
JITOptions jitOptions = new JITOptions();
CUlinkState state = new CUlinkState();
cuLinkCreate(jitOptions, state);
cuLinkAddFile(state, CU_JIT_INPUT_LIBRARY, LIBRARY_PATH, jitOptions);
cuLinkAddData(state, CU_JIT_INPUT_PTX, Pointer.to(ptxData), ptxData.length, "input.ptx", jitOptions);
long size[] = { 0 };
Pointer image = new Pointer();
cuLinkComplete(state, image, size);
module = new CUmodule();
cuModuleLoadDataEx(module, image, 0, new int[0], Pointer.to(new int[0]));
cuLinkDestroy(state);
for (int i = 0; i < kernelNames.length; i++) {
// Find the function in the source by name, get its pointer
functions[i] = new CUfunction();
cuModuleGetFunction(functions[i] , module, kernelNames[i]);
}
return functions;
}
return functions;
}
static String readFileAsString(String path)
{
......
src/main/java/com/elphel/imagej/tileprocessor/ImageDtt.java
View file @ 907cda8d
......@@ -3867,7 +3867,9 @@ public class ImageDtt {
double [][] port_weights = new double[ports][tile_len];
double [][] color_avg = new double[numcol][tile_len];
double [][] rgba = new double[numcol + 1 + (keep_weights?(ports + numcol + 1):0)][];
// double [][] rgba = new double[numcol + 1 + (keep_weights?(ports + numcol + 1):0)][];
// need to pass keep_weights to the caller
double [][] rgba = new double[numcol + 1 + ports + (keep_weights?(numcol + 1):0)][];
int rms_start = numcol + 1 + ports;
if (keep_weights){
for (int ncol = 0; ncol <= numcol ; ncol++) if ((ncol == numcol) || (iclt_tile[0][ncol] != null)) {
......@@ -4069,8 +4071,11 @@ public class ImageDtt {
rgba[ncol] = color_avg[ncol];
}
rgba[numcol] = alpha;
for (int i = 0; i < ports; i++) rgba[numcol + 1 + i] = port_weights[i];
// if (keep_weights){
for (int i = 0; i < ports; i++) {
rgba[numcol + 1 + i] = port_weights[i];
}
// }
if (max_diff != null){
for (int ip = 0; ip < ports; ip++){
max_diff[ip] = 0;
......@@ -5026,7 +5031,7 @@ public class ImageDtt {
System.out.println("iclt_2d():sharp_alpha= "+sharp_alpha);
}
boolean has_weights = false;
boolean set_has_weight = false;
boolean set_has_weight = false; // not used
for (int i = 0; (i < tilesY) && !set_has_weight; i++){
for (int j = 0; (j < tilesX) && !set_has_weight; j++){
if (texture_tiles[i][j] != null) {
......@@ -5064,15 +5069,15 @@ public class ImageDtt {
int n_half = transform_size / 2;
int lastY = tilesY-1;
int lastX = tilesX-1;
int offset = n_half * (transform_size * tilesX) + n_half;
int offset = n_half * (transform_size * tilesX) + n_half; // 4 pixels left and down (right/up when subtracted below)
for (int nTile = ai.getAndIncrement(); nTile < tiles_list[nser.get()].length; nTile = ai.getAndIncrement()) {
tileX = tiles_list[nser.get()][nTile][0];
tileY = tiles_list[nser.get()][nTile][1];
double [][] texture_tile =texture_tiles[tileY][tileX];
if (texture_tile != null) {
if (overlap) {
if ((tileY >0) && (tileX > 0) && (tileY < lastY) && (tileX < lastX)) { // fast, no extra checks
for (int i = 0; i < n2;i++){
if ((tileY >0) && (tileX > 0) && (tileY < lastY) && (tileX < lastX)) { // fast, no extra checks - ignore first/last rows and columns
for (int i = 0; i < n2; i++){
int start_line = ((tileY*transform_size + i) * tilesX + tileX)*transform_size - offset;
for (int chn = 0; chn < texture_tile.length; chn++) {
int schn = chn;
......@@ -5082,6 +5087,7 @@ public class ImageDtt {
if (texture_tile[schn] == null) {
dpixels[chn] = null;
} else {
// should it be better to multiply each color by alpha before accumulating? No, it is already windowed!
if ((chn != 3) || !sharp_alpha) {
for (int j = 0; j<n2;j++) {
dpixels[chn][start_line + j] += texture_tile[schn][n2 * i + j];
......@@ -9278,6 +9284,14 @@ public class ImageDtt {
}
}
}
// fix: removing extra slices
if (!clt_parameters.keep_weights && (texture_tiles[tileY][tileX]!=null)) {
if (numcol == 3 ) {
texture_tiles[tileY][tileX] = new double[][] {texture_tiles[tileY][tileX][0],texture_tiles[tileY][tileX][1],texture_tiles[tileY][tileX][2],texture_tiles[tileY][tileX][3]};
} else {
texture_tiles[tileY][tileX] = new double[][] {texture_tiles[tileY][tileX][0],texture_tiles[tileY][tileX][1]};
}
}
}
public double [][] get2DCorrs(
......
src/main/java/com/elphel/imagej/tileprocessor/QuadCLT.java
View file @ 907cda8d
......@@ -8985,6 +8985,7 @@ public class QuadCLT {
tp.clt_3d_passes.add(latest_scan); // put it back
}
int next_pass = tp.clt_3d_passes.size(); //
// Create tasks to scan, have tasks, disparity and border tiles in tp.clt_3d_passes
tp.thirdPassSetupSurf( // prepare tile tasks for the second pass based on the previous one(s) // needs last scan
clt_parameters,
//FIXME: make a special parameter?
......@@ -9564,6 +9565,7 @@ public class QuadCLT {
double [] alpha_zero = new double [4*image_dtt.transform_size*image_dtt.transform_size];
int alpha_index = 3;
for (int i = 0; i < alpha_zero.length; i++) alpha_zero[i]=0.0;
// border tiles are copied, alpha from alphaFade (not multiplied?)
for (int tileY = 0; tileY < tilesY; tileY++){
for (int tileX = 0; tileX < tilesX; tileX++){
texture_tiles_cluster[tileY][tileX]= null;
......@@ -9607,7 +9609,7 @@ public class QuadCLT {
texture_overlap[alpha_index][i] = d;
}
}
// for now - use just RGB. Later add option for RGBA
// for now - use just RGB. Later add option for RGBA (?)
double [][] texture_rgb = {texture_overlap[0],texture_overlap[1],texture_overlap[2]};
double [][] texture_rgba = {texture_overlap[0],texture_overlap[1],texture_overlap[2],texture_overlap[3]};
double [][] texture_rgbx = ((clt_parameters.alpha1 > 0)? texture_rgba: texture_rgb);
......
src/main/java/com/elphel/imagej/tileprocessor/TwoQuadCLT.java
View file @ 907cda8d
......@@ -2191,7 +2191,9 @@ public class TwoQuadCLT {
}
if (clt_parameters.show_rgba_color) {
int num_src_slices = 12 ; // calculate
int numcol = quadCLT_main.isMonochrome()?1:3;
int ports = imp_quad_main.length;
int num_src_slices = numcol + 1 + (clt_parameters.keep_weights?(ports + numcol + 1):0); // 12 ; // calculate
// float [][][] ftextures = gPUTileProcessor.getTextures(
// (is_mono?1:3), // int num_colors,
// clt_parameters.keep_weights); // boolean keep_weights);
......@@ -3533,7 +3535,7 @@ if (debugLevel > -100) return true; // temporarily !
}
}
quadCLT_main.writeKml(debugLevel ); // alos generated with x3d model
quadCLT_main.writeKml(debugLevel ); // also generated with x3d model
String jp4_copy_path= quadCLT_main.correctionsParameters.selectX3dDirectory(
set_name, // quad timestamp. Will be ignored if correctionsParameters.use_x3d_subdirs is false
......
src/main/java/com/elphel/imagej/x3d/export/X3dOutput.java
View file @ 907cda8d
......@@ -69,7 +69,7 @@ public class X3dOutput {
CLTParameters clt_parameters,
EyesisCorrectionParameters.CorrectionParameters correctionsParameters,
GeometryCorrection geometry_correction,
ArrayList <CLTPass3d> clt_3d_passes){
ArrayList <CLTPass3d> clt_3d_passes){ // to scan for textures, contain disp, tasks, border tiles
this.clt_parameters = clt_parameters;
this.correctionsParameters = correctionsParameters;
this.geometry_correction = geometry_correction;
......
src/main/resources/TileProcessor.cuh → src/main/resources/kernels/TileProcessor.cuh
View file @ 907cda8d
......@@ -66,6 +66,9 @@
#define CORR_OUT_RAD 4
#define FAT_ZERO_WEIGHT 0.0001 // add to port weights to avoid nan
#define THREADS_DYNAMIC_BITS 5 // treads in block for CDP creation of the texture list
#undef HAS_PRINTF
//7
//#define DEBUG1 1
//#define DEBUG2 1
......@@ -73,10 +76,11 @@
//#define DEBUG4 1
//#define DEBUG5 1
//#define DEBUG6 1
/*
#define DEBUG7 1
#define DEBUG8 1
#define DEBUG9 1
*/
#endif
//#define IMCLT14
......@@ -290,6 +294,63 @@ def set_imclt_sa(stride=9):
for d in sa8s[:-1]:
print('0x%02x,'%(d), end="")
print('0x%2x};'%(sa8s[-1]))
import numpy as np # math
def printAlphaFade(transform_size):
ts2 = 2 * transform_size
ts2m1 = ts2-1
alphaFade = np.zeros(shape=(16,ts2*ts2), dtype=float) # double [][] alphaFade = new double[16][ts2*ts2];
fade1d = np.zeros(shape=(16,), dtype=float) # double [] fade1d = new double [ts2];
for i in range (ts2):
fade1d[i] = 0.5 * (1.0 - np.cos(np.pi * (i +0.5) /ts2))
for i in range (ts2):
for j in range (ts2):
indx = i * ts2 + j
for m in range (16):
# if m == 0:
# alphaFade[m][indx] = 0
elif m == 1: # 0
alphaFade[m][indx] = fade1d[ts2m1 - i]
elif m == 2:
alphaFade[m][indx] = fade1d[j]
elif m == 4:
alphaFade[m][indx] = fade1d[i]
elif m == 8:
alphaFade[m][indx] = fade1d[ts2m1 - j]
elif m == 3:
alphaFade[m][indx] = (fade1d[ts2m1 - i],fade1d[j])[j > ts2m1 - i]
elif m == 6:
alphaFade[m][indx] = (fade1d[i],fade1d[j])[j > i]
elif m == 9:
alphaFade[m][indx] = (fade1d[ts2m1 - j],fade1d[ts2m1 - i])[j > i]
elif m == 12:
alphaFade[m][indx] = (fade1d[ts2m1 - j],fade1d[i])[i > ts2m1 - j]
else:
alphaFade[m][indx] = 1.0
floats_in_line=8
print("__constant__ float alphaFade[16][%d] = {"%(ts2*ts2))
for m in range (16):
for i in range (ts2 * ts2):
if ((i % floats_in_line) == 0):
print(" ",end="")
if (i == 0) :
print("{",end="")
else:
print(" ",end="")
print("%ff"%(alphaFade[m][i]), end ="")
if (((i + 1) % floats_in_line) == 0):
if (i == (ts2 * ts2 -1)):
print("}",end="")
else:
print(",")
else:
print(", ",end="")
if (m == 15):
print("};")
else:
print(",")
*/
......@@ -410,6 +471,521 @@ __constant__ int pairs[6][2]={
{1, 3},
{0, 3},
{2, 1}};
__constant__ float alphaFade[16][256] = {
{0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f,
0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f,
0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f,
0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f,
0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f,
0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f,
0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f, 0.000000f,
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//#endif
__device__ void convertCorrectTile(
struct CltExtra * gpu_kernel_offsets, // [tileY][tileX][color]
......@@ -525,6 +1101,12 @@ __device__ void imclt_plane( // not implemented, not used
float * gpu_rbg, // WIDTH, HEIGHT
const size_t dstride); // in floats (pixels)
__global__ void clear_texture_list(
int * gpu_texture_indices,// packed tile + bits (now only (1 << 7)
int width, // <= TILESX, use for faster processing of LWIR images
int height); // <= TILESY, use for faster processing of LWIR images
extern "C"
__global__ void correlate2D(
float ** gpu_clt, // [NUM_CAMS] ->[TILESY][TILESX][NUM_COLORS][DTT_SIZE*DTT_SIZE]
......@@ -793,6 +1375,54 @@ Java code:
#endif
}
#define USE_CDP
#ifdef USE_CDP
/**
* prepare list of texture tiles, woi, and calculate orthogonal neighbors for tiles (in 4 bits of the task field
* use 4x8=32 threads,
*/
extern "C"
__global__ void prepare_texture_list(
struct tp_task * gpu_tasks,
int num_tiles, // number of tiles in task list
int * gpu_texture_indices,// packed tile + bits (now only (1 << 7)
int * num_texture_tiles, // number of texture tiles to process
int * woi, // x,y,width,height of the woi
int width, // <= TILESX, use for faster processing of LWIR images
int height) // <= TILESY, use for faster processing of LWIR images
{
// int task_num = blockIdx.x;
// int tid = threadIdx.x; // maybe it will be just <<<1,1>>>
dim3 threads((1 << THREADS_DYNAMIC_BITS), 1, 1);
int blocks_x = (width + 1) >> THREADS_DYNAMIC_BITS;
dim3 blocks (blocks_x, height, 1);
if (threadIdx.x == 0) {
clear_texture_list<<<blocks,threads>>>(
gpu_texture_indices,
width,
height);
cudaDeviceSynchronize(); // not needed yet, just for testing
}
__syncthreads();
}
// blockDim.x * gridDim.x >= width
__global__ void clear_texture_list(
int * gpu_texture_indices,// packed tile + bits (now only (1 << 7)
int width, // <= TILESX, use for faster processing of LWIR images
int height) // <= TILESY, use for faster processing of LWIR images
{
int col = threadIdx.x + blockDim.x * blockIdx.x;
int row = blockIdx.y;
if (col > width) {
return;
}
*(gpu_texture_indices + col + row * TILESX) = 0.0;
}
#endif //#ifdef USE_CDP
extern "C"
......@@ -1569,12 +2199,14 @@ __device__ void corrUnfoldTile(
__device__ void debug_print_lpf(
float * lpf_tile)
{
#ifdef HAS_PRINTF
for (int dbg_row = 0; dbg_row < DTT_SIZE; dbg_row++){
for (int dbg_col = 0; dbg_col < DTT_SIZE; dbg_col++){
printf ("%10.5f ", lpf_tile[dbg_row * DTT_SIZE + dbg_col]);
}
printf("\n");
}
#endif
}
......@@ -1583,6 +2215,7 @@ __device__ void debug_print_clt1(
const int color,
int mask)
{
#ifdef HAS_PRINTF
if (color >= 0) printf("----------- Color = %d -----------\n",color);
for (int dbg_quadrant = 0; dbg_quadrant < 4; dbg_quadrant++){
printf("----------- Quadrant (c(h)-c(v), s-c, c-s, s-s) = %d -----------\n",dbg_quadrant);
......@@ -1596,6 +2229,7 @@ __device__ void debug_print_clt1(
}
printf("\n");
}
#endif
}
__device__ void debug_print_clt_scaled(
float * clt_tile, // [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports)
......@@ -1603,6 +2237,7 @@ __device__ void debug_print_clt_scaled(
int mask,
float scale)
{
#ifdef HAS_PRINTF
if (color >= 0) printf("----------- Color = %d -----------\n",color);
for (int dbg_quadrant = 0; dbg_quadrant < 4; dbg_quadrant++){
printf("----------- Quadrant (c(h)-c(v), s-c, c-s, s-s) = %d -----------\n",dbg_quadrant);
......@@ -1616,6 +2251,7 @@ __device__ void debug_print_clt_scaled(
}
printf("\n");
}
#endif
}
......@@ -1624,7 +2260,7 @@ __device__ void debug_print_mclt(
float * mclt_tile, // [4][DTT_SIZE][DTT_SIZE1], // +1 to alternate column ports)
const int color)
{
#ifdef HAS_PRINTF
if (color >= 0) printf("----------- Color = %d -----------\n",color);
for (int dbg_row = 0; dbg_row < DTT_SIZE2; dbg_row++){
for (int dbg_col = 0; dbg_col < DTT_SIZE2; dbg_col++){
......@@ -1633,6 +2269,7 @@ __device__ void debug_print_mclt(
printf("\n");
}
printf("\n");
#endif
}
__device__ void debug_print_corr_15x15(
......@@ -1640,6 +2277,7 @@ __device__ void debug_print_corr_15x15(
float * mclt_tile, //DTT_SIZE2M1 x DTT_SIZE2M1
const int color)
{
#ifdef HAS_PRINTF
int size2r1 = 2 * corr_radius + 1;
if (color >= 0) printf("----------- Color = %d -----------\n",color);
for (int dbg_row = 0; dbg_row < size2r1; dbg_row++){
......@@ -1649,6 +2287,7 @@ __device__ void debug_print_corr_15x15(
printf("\n");
}
printf("\n");
#endif
}
......
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