c++ - 避免在共享库之间传递数据的开销

Question

在1st共享库中，3D坐标数据以Point结构存储:

struct Point {

    float x{0}, y{0}, z{0};

};

std::vector<Point> *m_points;

在 2nd 共享库中，3D 坐标数据存储在 PointContainer 类中

class PointContainer : public QObject
{
    Q_OBJECT

    // This is a sophisticated class ...

public:
    QVector3D m_coord;
}

QVector<PointContainer> *m_points;

---

要将数据从2nd 共享库传递到1st，我使用了一个循环:

std::vector<Point> data(number_of_points);
// Prepare the data in the structure needed by the 1st shared library
    for (size_t i = 0; i < number_of_points; ++i) {
        float x = m_points->at(i).m_coord.x();
        float y = m_points->at(i).m_coord.y();
        float z = m_points->at(i).m_coord.z();
        Point point = {};
        point.x = x;
        point.y = y;
        point.z = z;
        data[i] = point;
    }
// Now pass data to the 1st shared library

number_of_points 可能很大，并且上述循环的计算量可能很大。有没有办法避免上述循环？我尝试在共享库中存储具有相同结构的数据，但这需要对代码进行大修。不确定是否还有其他选择，只是询问。

Answer 1

这段代码会更简洁一点，速度也稍微快一点:

std::vector<Point> data(number_of_points);
// Prepare the data in the structure needed by the 1st shared library
for (size_t i = 0; i < number_of_points; ++i) {
    const auto& source = (*m_points)[i].m_coord;
    data[i] = {source.x(), source.y(), source.z()};
}
// Now pass data to the 1st shared library

如果您的点数至少数千万，您可以使用 OpenMP 或英特尔 TBB 的 parallel_for 加速此循环。