changing corr2D to CDP (4fb94627) · Commits · Elphel / imagej-elphel

src/main/java/com/elphel/imagej/gpu/GPUTileProcessor.java

+35 −16

Original line number	Diff line number	Diff line
		@@ -190,6 +190,7 @@ public class GPUTileProcessor {
		private CUdeviceptr gpu_clt = new CUdeviceptr();
		private CUdeviceptr gpu_4_images = new CUdeviceptr();
		private CUdeviceptr gpu_corr_indices = new CUdeviceptr(); // allocate tilesX * tilesY * 6 * Sizeof.POINTER
		private CUdeviceptr gpu_num_corr_tiles = 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 CUdeviceptr gpu_woi = new CUdeviceptr(); // 4 integers (x, y, width, height) Rectangle - in tiles
		@@ -575,8 +576,8 @@ public class GPUTileProcessor {
		cuMemAlloc(gpu_tasks, tilesX * tilesY * TPTASK_SIZE * Sizeof.FLOAT);
		//=========== Seems that in many places Sizeof.POINTER (==8) is used instead of Sizeof.FLOAT !!! ============
		// Set corrs array
		/// cuMemAlloc(gpu_corrs, tilesX * tilesY * NUM_PAIRS * CORR_SIZE * Sizeof.POINTER);
		cuMemAlloc(gpu_corr_indices, tilesX * tilesY * NUM_PAIRS * Sizeof.POINTER);
		cuMemAlloc(gpu_corr_indices, tilesX * tilesY * NUM_PAIRS * Sizeof.FLOAT);
		cuMemAlloc(gpu_num_corr_tiles, 1 * Sizeof.FLOAT);

		//#define TILESYA ((TILESY +3) & (~3))
		int tilesYa = (tilesY + 3) & ~3;
		@@ -1119,7 +1120,7 @@ public class GPUTileProcessor {
		cuCtxSynchronize(); // remove later
		}

		public void execConverDirect() {
		public void execConvertDirect() {
		if (GPU_CONVERT_DIRECT_kernel == null)
		{
		IJ.showMessage("Error", "No GPU kernel: GPU_CONVERT_DIRECT_kernel");
		@@ -1206,20 +1207,24 @@ public class GPUTileProcessor {
		float fscale0 = (float) scales[0];
		float fscale1 = (num_colors >1)?((float) scales[1]):0.0f;
		float fscale2 = (num_colors >2)?((float) scales[2]):0.0f;
		int [] GridFullWarps = {(num_corr_tiles + CORR_TILES_PER_BLOCK-1) / CORR_TILES_PER_BLOCK,1,1};
		int [] ThreadsFullWarps = {CORR_THREADS_PER_TILE, CORR_TILES_PER_BLOCK, 1};
		// int [] GridFullWarps = {(num_corr_tiles + CORR_TILES_PER_BLOCK-1) / CORR_TILES_PER_BLOCK,1,1};
		// int [] ThreadsFullWarps = {CORR_THREADS_PER_TILE, CORR_TILES_PER_BLOCK, 1};
		int [] GridFullWarps = {1, 1, 1};
		int [] ThreadsFullWarps = {1, 1, 1};
		Pointer kernelParameters = Pointer.to(
		Pointer.to(gpu_clt),
		Pointer.to(new int[] { num_colors }),
		Pointer.to(new float[] {fscale0 }),
		Pointer.to(new float[] {fscale1 }),
		Pointer.to(new float[] {fscale2 }),
		Pointer.to(new float[] {(float) fat_zero }),
		Pointer.to(new int[] { num_corr_tiles }), // lpf_mask
		Pointer.to(gpu_corr_indices),
		Pointer.to(new int[] { corr_stride }),
		Pointer.to(new int[] { corr_radius }),
		Pointer.to(gpu_corrs) // lpf_mask
		Pointer.to(gpu_clt), // float ** gpu_clt,
		Pointer.to(new int[] { num_colors }), // int colors, // number of colors (3/1)
		Pointer.to(new float[] {fscale0 }), // float scale0, // scale for R
		Pointer.to(new float[] {fscale1 }), // float scale1, // scale for B
		Pointer.to(new float[] {fscale2 }), // float scale2, // scale for G
		Pointer.to(new float[] {(float) fat_zero }),// float fat_zero, // here - absolute
		Pointer.to(gpu_tasks), // struct tp_task * gpu_tasks,
		Pointer.to(new int[] { num_task_tiles }), // int num_tiles // number of tiles in task
		Pointer.to(gpu_corr_indices), // int * gpu_corr_indices, // packed tile+pair
		Pointer.to(gpu_num_corr_tiles), // int * pnum_corr_tiles, // pointer to a number of tiles to process
		Pointer.to(new int[] { corr_stride }), // const size_t corr_stride, // in floats
		Pointer.to(new int[] { corr_radius }), // int corr_radius, // radius of the output correlation (7 for 15x15)
		Pointer.to(gpu_corrs) // float * gpu_corrs); // correlation output data
		);
		cuCtxSynchronize();
		// Call the kernel function
		@@ -1395,6 +1400,20 @@ public class GPUTileProcessor {
		}
		return corrs;
		}
		public int [] getCorrIndices() {
		float [] fnum_corrs = new float[1];
		cuMemcpyDtoH(Pointer.to(fnum_corrs), gpu_num_corr_tiles, 1 * Sizeof.FLOAT);
		int num_corrs = Float.floatToIntBits(fnum_corrs[0]);
		float [] fcorr_indices = new float [num_corrs];
		cuMemcpyDtoH(Pointer.to(fcorr_indices), gpu_corr_indices, num_corrs * Sizeof.FLOAT);
		int [] corr_indices = new int [num_corrs];
		for (int i = 0; i < num_corrs; i++) {
		corr_indices[i] = Float.floatToIntBits(fcorr_indices[i]);
		}
		num_corr_tiles = num_corrs;
		return corr_indices;

		}

		/**
		* Get woi and RBGA image from the GPU after execRBGA call as 2/4 slices.

src/main/java/com/elphel/imagej/tileprocessor/TwoQuadCLT.java

+5 −4

Original line number	Diff line number	Diff line
		@@ -2078,10 +2078,10 @@ public class TwoQuadCLT {
		use_aux); // boolean use_aux)


		int [] corr_indices = gPUTileProcessor.getCorrTasks(
		tp_tasks);
		// int [] corr_indices = gPUTileProcessor.getCorrTasks(
		// tp_tasks);
		// corr_indices array of integers to be passed to GPU
		gPUTileProcessor.setCorrIndices(corr_indices);
		// gPUTileProcessor.setCorrIndices(corr_indices);

		int [] texture_indices = gPUTileProcessor.getTextureTasks(
		tp_tasks);
		@@ -2119,7 +2119,7 @@ public class TwoQuadCLT {
		long startDirectConvert=System.nanoTime();

		for (int i = 0; i < NREPEAT; i++ ) {
		gPUTileProcessor.execConverDirect();
		gPUTileProcessor.execConvertDirect();
		}

		// run imclt;
		@@ -2221,6 +2221,7 @@ public class TwoQuadCLT {
		int tilesY = GPUTileProcessor.IMG_HEIGHT / GPUTileProcessor.DTT_SIZE;
		int [] wh = new int[2];
		if (clt_parameters.show_corr) {
		int [] corr_indices = gPUTileProcessor.getCorrIndices();
		float [][] corr2D = gPUTileProcessor.getCorr2D(
		clt_parameters.gpu_corr_rad); // int corr_rad);
		// convert to 6-layer image using tasks

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