mirror of
https://github.com/NVIDIA/cuda-samples.git
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208 lines
6.5 KiB
Plaintext
208 lines
6.5 KiB
Plaintext
/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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#include <stdio.h>
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#include <cuda_runtime_api.h>
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#include <helper_cuda.h>
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#include <string.h>
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__forceinline__ __device__ float2 operator+(float2 a, float2 b) {
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float2 c;
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c.x = a.x + b.x;
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c.y = a.y + b.y;
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return c;
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}
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__forceinline__ __device__ float2 operator-(float2 a, float2 b) {
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float2 c;
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c.x = a.x - b.x;
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c.y = a.y - b.y;
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return c;
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}
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__forceinline__ __device__ float2 operator*(float a, float2 b) {
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float2 c;
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c.x = a * b.x;
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c.y = a * b.y;
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return c;
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}
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__forceinline__ __device__ float length(float2 a) {
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return sqrtf(a.x * a.x + a.y * a.y);
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}
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#define MAX_TESSELLATION 32
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struct BezierLine {
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float2 CP[3];
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float2 *vertexPos;
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int nVertices;
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};
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__global__ void computeBezierLinePositions(int lidx, BezierLine *bLines,
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int nTessPoints) {
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int idx = threadIdx.x + blockDim.x * blockIdx.x;
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if (idx < nTessPoints) {
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float u = (float)idx / (float)(nTessPoints - 1);
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float omu = 1.0f - u;
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float B3u[3];
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B3u[0] = omu * omu;
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B3u[1] = 2.0f * u * omu;
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B3u[2] = u * u;
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float2 position = {0, 0};
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for (int i = 0; i < 3; i++) {
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position = position + B3u[i] * bLines[lidx].CP[i];
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}
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bLines[lidx].vertexPos[idx] = position;
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}
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}
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__global__ void computeBezierLinesCDP(BezierLine *bLines, int nLines) {
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int lidx = threadIdx.x + blockDim.x * blockIdx.x;
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if (lidx < nLines) {
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float curvature = length(bLines[lidx].CP[1] -
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0.5f * (bLines[lidx].CP[0] + bLines[lidx].CP[2])) /
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length(bLines[lidx].CP[2] - bLines[lidx].CP[0]);
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int nTessPoints = min(max((int)(curvature * 16.0f), 4), MAX_TESSELLATION);
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if (bLines[lidx].vertexPos == NULL) {
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bLines[lidx].nVertices = nTessPoints;
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cudaMalloc((void **)&bLines[lidx].vertexPos,
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nTessPoints * sizeof(float2));
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}
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computeBezierLinePositions<<<ceilf((float)bLines[lidx].nVertices / 32.0f),
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32>>>(lidx, bLines, bLines[lidx].nVertices);
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}
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}
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__global__ void freeVertexMem(BezierLine *bLines, int nLines) {
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int lidx = threadIdx.x + blockDim.x * blockIdx.x;
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if (lidx < nLines) cudaFree(bLines[lidx].vertexPos);
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}
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unsigned int checkCapableSM35Device(int argc, char **argv) {
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// Get device properties
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cudaDeviceProp properties;
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int device_count = 0, device = -1;
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if (checkCmdLineFlag(argc, (const char **)argv, "device")) {
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device = getCmdLineArgumentInt(argc, (const char **)argv, "device");
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cudaDeviceProp properties;
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checkCudaErrors(cudaGetDeviceProperties(&properties, device));
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if (properties.major > 3 ||
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(properties.major == 3 && properties.minor >= 5)) {
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printf("Running on GPU %d (%s)\n", device, properties.name);
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} else {
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printf(
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"cdpBezierTessellation requires GPU devices with compute SM 3.5 or "
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"higher.");
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printf("Current GPU device has compute SM %d.%d. Exiting...\n",
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properties.major, properties.minor);
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return EXIT_FAILURE;
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}
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} else {
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checkCudaErrors(cudaGetDeviceCount(&device_count));
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for (int i = 0; i < device_count; ++i) {
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checkCudaErrors(cudaGetDeviceProperties(&properties, i));
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if (properties.major > 3 ||
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(properties.major == 3 && properties.minor >= 5)) {
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device = i;
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printf("Running on GPU %d (%s)\n", i, properties.name);
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break;
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}
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printf("GPU %d %s does not support CUDA Dynamic Parallelism\n", i,
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properties.name);
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}
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}
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if (device == -1) {
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fprintf(stderr,
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"cdpBezierTessellation requires GPU devices with compute SM 3.5 or "
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"higher. Exiting...\n");
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return EXIT_WAIVED;
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}
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return EXIT_SUCCESS;
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}
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#define N_LINES 256
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#define BLOCK_DIM 64
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int main(int argc, char **argv) {
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BezierLine *bLines_h = new BezierLine[N_LINES];
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float2 last = {0, 0};
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for (int i = 0; i < N_LINES; i++) {
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bLines_h[i].CP[0] = last;
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for (int j = 1; j < 3; j++) {
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bLines_h[i].CP[j].x = (float)rand() / (float)RAND_MAX;
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bLines_h[i].CP[j].y = (float)rand() / (float)RAND_MAX;
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}
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last = bLines_h[i].CP[2];
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bLines_h[i].vertexPos = NULL;
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bLines_h[i].nVertices = 0;
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}
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unsigned int sm35Ret = checkCapableSM35Device(argc, argv);
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if (sm35Ret != EXIT_SUCCESS) {
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exit(sm35Ret);
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}
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BezierLine *bLines_d;
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checkCudaErrors(cudaMalloc((void **)&bLines_d, N_LINES * sizeof(BezierLine)));
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checkCudaErrors(cudaMemcpy(bLines_d, bLines_h, N_LINES * sizeof(BezierLine),
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cudaMemcpyHostToDevice));
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printf("Computing Bezier Lines (CUDA Dynamic Parallelism Version) ... ");
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computeBezierLinesCDP<<<(unsigned int)ceil((float)N_LINES / (float)BLOCK_DIM),
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BLOCK_DIM>>>(bLines_d, N_LINES);
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printf("Done!\n");
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// Do something to draw the lines here
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freeVertexMem<<<(unsigned int)ceil((float)N_LINES / (float)BLOCK_DIM),
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BLOCK_DIM>>>(bLines_d, N_LINES);
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checkCudaErrors(cudaFree(bLines_d));
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delete[] bLines_h;
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exit(EXIT_SUCCESS);
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}
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