// // Created by 14727 on 2022/11/7. // #include #include "NurbsEvaluator.cuh" #include "cstdio" #include "utils.h" //#include "NurbsBasis.cuh" //extern __device__ void NurbsBasis::d_basisFunction(float *N_Texture, const float *knots, float u, int degree, int d_knotsCnt) {}; __host__ NurbsSurface::Evaluator::Evaluator(std::vector>> controlPoints, std::vector knots_u, std::vector knots_v) { this->knots_u = std::move(knots_u); this->knots_v = std::move(knots_v); this->controlPoints = std::move(controlPoints); recordTime = false; d_nTexture_u = nullptr; d_nTexture_v = nullptr; d_nTexture1_u = nullptr; d_nTexture1_v = nullptr; d_knots_u = nullptr; d_knots_v = nullptr; d_points = nullptr; } __host__ std::vector, std::vector>> NurbsSurface::Evaluator::evaluate(int sampleCnt_u_, int sampleCnt_v_) { sampleCnt_u = sampleCnt_u_; sampleCnt_v = sampleCnt_v_; printf("outside printf..\n"); // NurbsBasis::myPrint11(1, 3); // 构造指向device的controlPoints const int pointsCnt_u = controlPoints.size(), pointsCnt_v = controlPoints[0].size(), pointSize = controlPoints[0][0].size(); const int pointsBytes = pointsCnt_u * pointsCnt_v * pointSize * sizeof(float); auto *h_points = (float *) malloc(pointsBytes); for (int i = 0; i < pointsCnt_u; i++) { for (int j = 0; j < pointsCnt_v; j++) { for (int k = 0; k < pointSize; k++) { h_points[(i * pointsCnt_v + j) * pointSize + k] = controlPoints[i][j][k]; } } } cudaMalloc((void **) &d_points, pointsBytes); cudaMemcpy(d_points, h_points, pointsBytes, cudaMemcpyHostToDevice); // 构造指向device的knots const int knotsCnt_u = knots_u.size(), knotsCnt_v = knots_v.size(); const int knotsBytes_u = knotsCnt_u * sizeof(float), knotsBytes_v = knotsCnt_v * sizeof(float); auto *h_knots_u = (float *) malloc(knotsBytes_u), *h_knots_v = (float *) malloc(knotsBytes_v); for (int i = 0; i < knotsCnt_u; i++) h_knots_u[i] = knots_u[i]; for (int i = 0; i < knotsCnt_v; i++) h_knots_v[i] = knots_v[i]; cudaMalloc((void **) &d_knots_u, knotsBytes_u); cudaMalloc((void **) &d_knots_v, knotsBytes_v); cudaMemcpy(d_knots_u, h_knots_u, knotsBytes_u, cudaMemcpyHostToDevice); cudaMemcpy(d_knots_v, h_knots_v, knotsBytes_v, cudaMemcpyHostToDevice); // 构造nTexture cudaMalloc((void **) &d_nTexture_u, sampleCnt_u * pointsCnt_u * sizeof(float)); // 注意nTexture的大小,在算梯度时用得到i=pointsCnt + 1的基函数值 cudaMalloc((void **) &d_nTexture_v, sampleCnt_v * pointsCnt_v * sizeof(float)); // 构造nTexture1 cudaMalloc((void **) &d_nTexture1_u, sampleCnt_u * (pointsCnt_u + 1) * sizeof(float)); cudaMalloc((void **) &d_nTexture1_v, sampleCnt_v * (pointsCnt_v + 1) * sizeof(float)); // 构造g_basisTexture线程层级 dim3 blockBasis(512); dim3 gridBasis_u((sampleCnt_u + blockBasis.x - 1) / blockBasis.x); dim3 gridBasis_v((sampleCnt_v + blockBasis.x - 1) / blockBasis.x); // 构造线程层级,调用核函数 dim3 block(32, 32); dim3 grid((sampleCnt_u + block.x - 1) / block.x, (sampleCnt_v + block.y - 1) / block.y); // 记录用时 double time_cost_device; g_basisTexture<<>>(d_nTexture_u, d_nTexture1_u, d_knots_u, pointsCnt_u, knotsCnt_u, sampleCnt_u); cudaDeviceSynchronize(); g_basisTexture<<>>(d_nTexture_v, d_nTexture1_v, d_knots_v, pointsCnt_v, knotsCnt_v, sampleCnt_v); cudaDeviceSynchronize(); if (recordTime) time_cost_device = utils::get_time_windows(); g_evaluate <<>>(d_nTexture_u, d_nTexture_v, d_points, pointsCnt_u, pointsCnt_v, pointSize, knots_u[knotsCnt_u - 1], knots_v[knotsCnt_v - 1], sampleCnt_u, sampleCnt_v); cudaDeviceSynchronize(); // 所用线程结束后再获取结束时间。cudaThreadSynchronize()在CUDA1.0后被弃用 if (recordTime) { time_cost_device = utils::get_time_windows() - time_cost_device; printf("GPU time cost of surface evaluation for %d samples: %lf\n", sampleCnt_u * sampleCnt_v, time_cost_device); } // 释放内存 free(h_points); free(h_knots_u); free(h_knots_v); printf("First derivatives and normal vectors calculated by GPU:\n"); derivative(); cudaDeviceReset(); return {}; } __host__ std::vector>> NurbsCurve::Evaluator::evaluate(int sampleCnt_) { this->sampleCnt = sampleCnt_; // 构造指向device的controlPoints const int pointsCnt = controlPoints.size(), pointSize = controlPoints[0].size(); const int pointsBytes = pointsCnt * pointSize * sizeof(float); auto *h_points = (float *) malloc(pointsBytes); for (int i = 0; i < pointsCnt; i++) { for (int j = 0; j < pointSize; j++) { h_points[i * pointSize + j] = controlPoints[i][j]; } } cudaMalloc((void **) &d_points, pointsBytes); cudaMemcpy(d_points, h_points, pointsBytes, cudaMemcpyHostToDevice); // 构造指向device的knots const int knotsCnt = knots.size(); const int knotsBytes = knotsCnt * sizeof(float); auto *h_knots = (float *) malloc(knotsBytes); for (int i = 0; i < knotsCnt; i++) h_knots[i] = knots[i]; cudaMalloc((void **) &d_knots, knotsBytes); cudaMemcpy(d_knots, h_knots, knotsBytes, cudaMemcpyHostToDevice); // 分配nTexture的内存。只需要GPU内存 // float *d_nTexture = nullptr; cudaMalloc((void **) &d_nTexture, sampleCnt * pointsCnt * sizeof(float)); // 注意nTexture的大小,在算梯度时用得到i=pointsCnt + 1的基函数值 // 分配nTexture1的内存。只需要GPU内存 // float *d_nTexture1 = nullptr; cudaMalloc((void **) &d_nTexture1, sampleCnt * (pointsCnt + 1) * sizeof(float)); // 构造g_basisTexture线程层级 dim3 blockBasis(512); dim3 gridBasis((sampleCnt + blockBasis.x - 1) / blockBasis.x); // 构造线程层级 dim3 block(32, 32); dim3 grid((sampleCnt + block.x * block.y - 1) / (block.x * block.y)); // 记录用时 double time_cost_device; if (recordTime) time_cost_device = utils::get_time_windows(); printf("there..\n"); g_basisTexture <<>>(d_nTexture, d_nTexture1, d_knots, pointsCnt, knotsCnt, sampleCnt); // cudaMemcpy(d_nTextureCpy, d_nTexture, nTextureBytes, cudaMemcpyDeviceToDevice); // 有同步功能 cudaDeviceSynchronize(); printf("here..\n"); g_evaluate <<>>(d_nTexture, d_points, pointsCnt, pointSize, knots[knotsCnt - 1], sampleCnt); // g_test<<<1,6>>>(d_nTextureCpy); cudaDeviceSynchronize(); // 所用线程结束后再获取结束时间。cudaThreadSynchronize()在CUDA1.0后被弃用 if (recordTime) { time_cost_device = utils::get_time_windows() - time_cost_device; printf("GPU time cost of curve evaluation for %d samples: %lf\n", sampleCnt, time_cost_device); } free(h_points); free(h_knots); printf("First derivatives calculated by GPU:\n"); derivative(); cudaDeviceReset(); return {}; } __host__ void NurbsSurface::Evaluator::derivative() { float *d_derTexture_u = nullptr; float *d_derTexture_v = nullptr; const int pointsCnt_u = controlPoints.size(), pointsCnt_v = controlPoints[0].size(), pointSize = controlPoints[0][0].size(); const int knotsCnt_u = knots_u.size(), knotsCnt_v = knots_v.size(); cudaMalloc((void **) &d_derTexture_u, sampleCnt_u * pointsCnt_u * sizeof(float)); cudaMalloc((void **) &d_derTexture_v, sampleCnt_v * pointsCnt_v * sizeof(float)); // 构造线程层级 dim3 block(32, 32); dim3 grid((sampleCnt_u + block.x - 1) / block.x, (sampleCnt_v + block.y - 1) / block.y); // 构造g_basisTexture线程层级 dim3 blockTex(512); dim3 gridTex_u((sampleCnt_u + blockTex.x - 1) / blockTex.x); dim3 gridTex_v((sampleCnt_v + blockTex.x - 1) / blockTex.x); // 记录用时 double time_cost_device; if (recordTime) time_cost_device = utils::get_time_windows(); g_derTexture<<>>(d_derTexture_u, d_nTexture1_u, d_knots_u, pointsCnt_u, knotsCnt_u, sampleCnt_u); g_derTexture<<>>(d_derTexture_v, d_nTexture1_v, d_knots_v, pointsCnt_v, knotsCnt_v, sampleCnt_v); cudaDeviceSynchronize(); g_derivative<<>>(d_derTexture_u, d_derTexture_v, d_nTexture_u, d_nTexture_v, d_points, pointsCnt_u, pointsCnt_v, pointSize, knots_u[knotsCnt_u - 1], knots_v[knotsCnt_v - 1], sampleCnt_u, sampleCnt_v); cudaDeviceSynchronize(); // 所用线程结束后再获取结束时间。cudaThreadSynchronize()在CUDA1.0后被弃用 if (recordTime) { time_cost_device = utils::get_time_windows() - time_cost_device; printf("GPU time cost of surface first derivative calculating for %d samples: %lf\n", sampleCnt_u * sampleCnt_v, time_cost_device); } cudaFree(d_derTexture_u); cudaFree(d_derTexture_v); } __host__ void NurbsCurve::Evaluator::derivative() { float *d_derTexture = nullptr; const int pointsCnt = controlPoints.size(), pointSize = controlPoints[0].size(); const int knotsCnt = knots.size(); cudaMalloc((void **) &d_derTexture, sampleCnt * pointsCnt * sizeof(float)); // 构造线程层级 dim3 block(32, 32); dim3 grid((sampleCnt + block.x * block.y - 1) / (block.x * block.y)); // 构造g_basisTexture线程层级 dim3 blockTex(512); dim3 gridTex((sampleCnt + blockTex.x - 1) / blockTex.x); // 记录用时 double time_cost_device; if (recordTime) time_cost_device = utils::get_time_windows(); g_derTexture<<>>(d_derTexture, d_nTexture1, d_knots, pointsCnt, knotsCnt, sampleCnt); cudaDeviceSynchronize(); g_derivative<<>>(d_derTexture, d_points, pointsCnt, pointSize, knots[knotsCnt - 1], sampleCnt); cudaDeviceSynchronize(); // 所用线程结束后再获取结束时间。cudaThreadSynchronize()在CUDA1.0后被弃用 if (recordTime) { time_cost_device = utils::get_time_windows() - time_cost_device; printf("GPU time cost of curve first derivative calculating for %d samples: %lf\n", sampleCnt, time_cost_device); } cudaFree(d_derTexture); } //__global__ void //NurbsSurface::g_evaluate(const float *d_points, const float *d_knots_u, const float *d_knots_v, // int d_pointsCnt_u, // int d_pointsCnt_v, int d_pointSize, int d_knotsCnt_u, int d_knotsCnt_v, // int d_sampleCnt_u, int d_sampleCnt_v) { //// printf(" surface calculating... \n"); // // 二维grid和二维的block // int ix = int(blockIdx.x * blockDim.x + threadIdx.x); // int iy = int(blockIdx.y * blockDim.y + threadIdx.y); // // float d_paramCeil_u = d_knots_u[d_knotsCnt_u - 1]; // float d_paramCeil_v = d_knots_v[d_knotsCnt_v - 1]; // // float u = ix * d_paramCeil_u / (d_sampleCnt_u - 1); // float v = iy * d_paramCeil_v / (d_sampleCnt_v - 1); // // if (u > 1.0 * d_paramCeil_u || v > 1.0 * d_paramCeil_v) { // return; // } // // int d_degree_u = d_knotsCnt_u - 1 - d_pointsCnt_u; // int d_degree_v = d_knotsCnt_v - 1 - d_pointsCnt_v; // // 注意,在device中,全局内存还是以malloc和free的方式分配和回收的,而不是使用cudaMalloc和cudaFree // auto *N_Texture_U = (float *) malloc((d_degree_u + 1) * (d_knotsCnt_u - 1) * sizeof(float)); // auto *N_Texture_V = (float *) malloc((d_degree_v + 1) * (d_knotsCnt_v - 1) * sizeof(float)); // d_basisFunction(N_Texture_U, d_knots_u, u, d_degree_u, d_knotsCnt_u); // d_basisFunction(N_Texture_V, d_knots_v, v, d_degree_v, d_knotsCnt_v); // float x = 0., y = 0., z = 0.; // for (int i = 0; i < d_pointsCnt_u; i++) { // for (int j = 0; j < d_pointsCnt_v; j++) { // float N_U = N_Texture_U[d_degree_u * (d_knotsCnt_u - 1) + i]; // float N_V = N_Texture_V[d_degree_v * (d_knotsCnt_v - 1) + j]; // int idx = (i * d_pointsCnt_v + j) * d_pointSize; // x += N_U * N_V * d_points[idx]; // y += N_U * N_V * d_points[idx + 1]; // z += N_U * N_V * d_points[idx + 2]; // } // } // printf("(%g, %g)-->(%g, %g, %g)\n", u, v, x, y, z); // %g输出,舍弃无意义的0 // free(N_Texture_U); // free(N_Texture_V); //} __global__ void NurbsSurface::g_evaluate(const float *d_nTexture_u, const float *d_nTexture_v, const float *d_points, int d_pointsCnt_u, int d_pointsCnt_v, int d_pointSize, float d_lastKnot_u, float d_lastKnot_v, int d_sampleCnt_u, int d_sampleCnt_v) { // 二维grid和二维的block int ix = blockIdx.x * blockDim.x + threadIdx.x; int iy = blockIdx.y * blockDim.y + threadIdx.y; float u = ix * d_lastKnot_u / (d_sampleCnt_u - 1); float v = iy * d_lastKnot_v / (d_sampleCnt_v - 1); if (u > 1.0 * d_lastKnot_u || v > 1.0 * d_lastKnot_v) { return; } float x = 0., y = 0., z = 0.; for (int i = 0; i < d_pointsCnt_u; i++) { float N_U = d_nTexture_u[ix * d_pointsCnt_u + i]; for (int j = 0; j < d_pointsCnt_v; j++) { float N_V = d_nTexture_v[iy * d_pointsCnt_v + j]; int idx = (i * d_pointsCnt_v + j) * d_pointSize; x += N_U * N_V * d_points[idx]; y += N_U * N_V * d_points[idx + 1]; z += N_U * N_V * d_points[idx + 2]; } } printf("(%g, %g)-->(%g, %g, %g)\n", u, v, x, y, z); // %g输出,舍弃无意义的0 } __global__ void NurbsSurface::g_derivative(const float *derTexture_u, const float *derTexture_v, const float *nTexture_u, const float *nTexture_v, const float *d_points, int d_pointsCnt_u, int d_pointsCnt_v, int d_pointSize, float d_lastKnot_u, float d_lastKnot_v, int d_sampleCnt_u, int d_sampleCnt_v) { // 二维grid和二维的block int ix = blockIdx.x * blockDim.x + threadIdx.x; int iy = blockIdx.y * blockDim.y + threadIdx.y; if (ix >= d_sampleCnt_u || iy >= d_sampleCnt_v) { return; } float u = ix * d_lastKnot_u / (d_sampleCnt_u - 1); float v = iy * d_lastKnot_v / (d_sampleCnt_v - 1); float x_u = 0., y_u = 0, z_u = 0.; float x_v = 0., y_v = 0, z_v = 0.; for (int i = 0; i < d_pointsCnt_u; i++) { for (int j = 0; j < d_pointsCnt_u; j++) { int baseIdx = (i * d_pointsCnt_v + j) * d_pointSize; float factor_u = derTexture_u[ix * d_pointsCnt_u + i] * nTexture_v[iy * d_pointsCnt_v + j]; float factor_v = derTexture_v[iy * d_pointsCnt_v + j] * nTexture_u[ix * d_pointsCnt_u + i]; x_u += factor_u * d_points[baseIdx]; y_u += factor_u * d_points[baseIdx + 1]; z_u += factor_u * d_points[baseIdx + 2]; x_v += factor_v * d_points[baseIdx]; y_v += factor_v * d_points[baseIdx + 1]; z_v += factor_v * d_points[baseIdx + 2]; } } float x_n = y_u * z_v - y_v * z_u, y_n = x_v * z_u - x_u * z_v, z_n = x_u * y_v - x_v * y_u; // 叉乘得到法向量 printf("(%g,%g)-->u:(%g, %g, %g), v:(%g,%g,%g), normal:(%g,%g,%g)\n", u, v, x_u, y_u, z_u, x_v, y_v, z_v, x_n, y_n, z_n); } __global__ void NurbsCurve::g_evaluate(const float *NTexture, const float *d_points, const int d_pointsCnt, const int d_pointSize, const float d_lastKnot, const int d_sampleCnt) { // printf(" curve calculating... \n"); // 二维grid和一维的block // int idx = (blockIdx.y * gridDim.x + blockIdx.x) * blockDim.x + threadIdx.x; // 二维block和一维grid int idx = blockIdx.x * blockDim.x * blockDim.y + threadIdx.y * blockDim.x + threadIdx.x; float u = idx * d_lastKnot / (d_sampleCnt - 1); if (u > 1.0 * d_lastKnot) { return; } // // int d_degree = d_knotsCnt - 1 - d_pointsCnt; // // 注意,在device中,全局内存还是以malloc和free的方式分配和回收的,而不是使用cudaMalloc和cudaFree // auto *N_dp = (float *) malloc((d_degree + 1) * (d_knotsCnt - 1) * sizeof(float)); // d_basisFunction(N_dp, d_knots, u, d_degree, d_knotsCnt); float x = 0., y = 0., z = 0.; for (int i = 0; i < d_pointsCnt; i++) { float N = NTexture[idx * d_pointsCnt + i]; int baseIdx = i * d_pointSize; x += N * d_points[baseIdx]; y += N * d_points[baseIdx + 1]; z += N * d_points[baseIdx + 2]; } printf("(%g)-->(%g, %g, %g)\n", u, x, y, z); // %g输出,舍弃无意义的0 } __global__ void NurbsCurve::g_derivative(const float *derTexture, const float *d_points, int d_pointsCnt, int d_pointSize, float d_lastKnot, int d_sampleCnt) { // 二维block和一维grid int idx = blockIdx.x * blockDim.x * blockDim.y + threadIdx.y * blockDim.x + threadIdx.x; if (idx >= d_sampleCnt) return; float u = idx * d_lastKnot / (d_sampleCnt - 1); float x = 0., y = 0, z = 0.; // printf("pointSize: %d\n", d_pointSize); for (int i = 0; i < d_pointsCnt; i++) { int baseIdx = i * d_pointSize; float nFactor = derTexture[idx * d_pointsCnt + i]; x += nFactor * d_points[baseIdx]; y += nFactor * d_points[baseIdx + 1]; z += nFactor * d_points[baseIdx + 2]; // printf("(x, y, z): (%g, %g, %g)\n", d_points[baseIdx], d_points[baseIdx + 1], d_points[baseIdx + 2]); } printf("(%g)-->(%g, %g, %g)\n", u, x, y, z); } __global__ void g_basisTexture(float *nTexture, float *nTexture1, const float *d_knots, int d_pointsCnt, int d_knotsCnt, int d_sampleCnt) { // 一维grid和一维block int idx = blockIdx.x * blockDim.x + threadIdx.x; // 采样点编号 float d_paramCeil = d_knots[d_knotsCnt - 1]; float u = idx * d_paramCeil / (d_sampleCnt - 1); if (u > 1.0 * d_paramCeil) { return; } int d_degree = d_knotsCnt - 1 - d_pointsCnt; auto *N_dp = (float *) malloc((d_degree + 1) * (d_knotsCnt - 1) * sizeof(float)); d_basisFunction(N_dp, d_knots, u, d_degree, d_knotsCnt); for (int i = 0; i < d_pointsCnt; i++) { nTexture[idx * d_pointsCnt + i] = N_dp[d_degree * (d_knotsCnt - 1) + i]; nTexture1[idx * (d_pointsCnt + 1) + i] = N_dp[(d_degree - 1) * (d_knotsCnt - 1) + i]; // printf("nTexture1: %g ", nTexture1[idx * (d_pointsCnt + 1) + i]); } nTexture1[idx * (d_pointsCnt + 1) + d_pointsCnt] = N_dp[(d_degree - 1) * (d_knotsCnt - 1) + d_pointsCnt]; // nTexture1多记录一列数据 free(N_dp); } __global__ void g_derTexture(float *derTexture, const float *nTexture1, const float *d_knots, int d_pointsCnt, int d_knotsCnt, int d_sampleCnt) { // 一维grid和一维block int idx = blockIdx.x * blockDim.x + threadIdx.x; // 采样点编号 if (idx >= d_sampleCnt) { return; } int degree = d_knotsCnt - 1 - d_pointsCnt; // printf("degree: %d\n", degree); for (int i = 0; i < d_pointsCnt; i++) { float left = d_floatEqual(d_knots[i + degree], d_knots[i]) ? 0 : nTexture1[idx * (d_pointsCnt + 1) + i] * (degree - 1) / (d_knots[i + degree] - d_knots[i]); float right = d_floatEqual(d_knots[i + degree + 1], d_knots[i + 1]) ? 0 : nTexture1[idx * (d_pointsCnt + 1) + i + 1] * (degree - 1) / (d_knots[i + degree + 1] - d_knots[i + 1]); derTexture[idx * d_pointsCnt + i] = left - right; // printf("<%d, %d> -- %g \n", idx, i, left - right); // printf("nTex1: %g \n", nTexture1[idx * (d_pointsCnt + 1) + i]); } } __host__ NurbsCurve::Evaluator::Evaluator(std::vector> controlPoints, std::vector knots) { this->knots = std::move(knots); this->controlPoints = std::move(controlPoints); recordTime = false; d_nTexture = nullptr; d_nTexture1 = nullptr; sampleCnt = 0; d_points = nullptr; d_knots = nullptr; } __device__ void d_basisFunction(float *N_Texture, const float *knots, float u, int degree, int d_knotsCnt) { int m = d_knotsCnt - 1; for (int p = 0; p <= degree; p++) { for (int i = 0; i + p <= m - 1; i++) { if (p == 0) { if ((u > knots[i] || d_floatEqual(u, knots[i])) && (u < knots[i + 1]) || d_floatEqual(u, knots[i + 1]) && d_floatEqual(u, knots[m])) { N_Texture[p * m + i] = 1.0; } else { N_Texture[p * m + i] = 0.0; } } else { float Nip_1 = N_Texture[(p - 1) * m + i]; float Ni1p_1 = N_Texture[(p - 1) * m + i + 1]; float left = d_floatEqual(knots[i + p], knots[i]) ? 0 : (u - knots[i]) * Nip_1 / (knots[i + p] - knots[i]); float right = d_floatEqual(knots[i + p + 1], knots[i + 1]) ? 0 : (knots[i + p + 1] - u) * Ni1p_1 / (knots[i + p + 1] - knots[i + 1]); N_Texture[p * m + i] = left + right; } } } } __device__ bool d_floatEqual(float a, float b) { return abs(a - b) < 0.00001; } void NurbsCurve::Evaluator::setRecordTime(bool r) { recordTime = r; } void NurbsSurface::Evaluator::setRecordTime(bool r) { recordTime = r; } NurbsSurface::Evaluator::~Evaluator() { cudaFree(d_nTexture_u); cudaFree(d_nTexture_v); cudaFree(d_nTexture1_u); cudaFree(d_nTexture1_v); cudaFree(d_points); cudaFree(d_knots_u); cudaFree(d_knots_v); } NurbsCurve::Evaluator::~Evaluator() { cudaFree(d_nTexture); cudaFree(d_nTexture1); cudaFree(d_points); cudaFree(d_knots); }