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What are the performance considerations in C++ generic programming?

Jun 02, 2024 pm 10:54 PM
c++ Generics

C Performance considerations for generic programming: Avoid over-segmentation: Generic algorithms may be instantiated multiple times, resulting in code segmentation and performance degradation. Avoid virtual calls: Generic classes or methods may generate virtual calls, thereby reducing performance. Consider specialization: For common types, creating type-specific implementations can avoid over-segmentation and virtual calls and improve performance.

C++ 泛型编程中的性能注意事项是什么?

Performance Considerations in Generic Programming in C

Generic programming is a powerful tool in C that allows us Write code that works with a variety of data types. However, when programming with generics, it's critical to understand their potential performance impact.

1. Avoid over-segmentation:

Generic algorithms may be instantiated multiple times depending on the type, resulting in code segmentation and performance degradation. Consider the following example:

template <typename T>
void swap(T& a, T& b) {
  T temp = a;
  a = b;
  b = temp;
}
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To exchange a value of type int, this function would be instantiated as swap<int>. Likewise, for a value of type double, it will be instantiated as swap<double>. This over-partitioning increases binary file size and execution time.

2. Avoid virtual calls:

Generic classes or methods may cause virtual calls, further reducing performance. For example:

class Base {
 public:
  virtual void doSomething();
};

template <typename T>
class Derived : public Base {
 public:
  void doSomething() override {
    // 重写 doSomething() 方法
  }
};
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Since doSomething() is a virtual method, each Derived<T> object will resolve to the correct implementation at runtime. This introduces an extra layer of indirection, hurting performance.

3. Consider specializations:

For some common types, such as int, double and bool, we can avoid over-segmentation and virtual calls by creating type-specific implementations. This is called specialization:

template <>
void swap<int>(int& a, int& b) {
  // 对 int 类型进行特殊处理
}
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Specialization can significantly improve performance because it eliminates multiple instantiations and virtual calls.

Practical case:

Suppose we have a Vector class that uses generic programming to store different types of data:

template <typename T>
class Vector {
 public:
  Vector(size_t size);
  ~Vector();

  // ...
};
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If we frequently swap the positions of elements in a Vector, it is recommended to create a type-specific swap() specialization for the T type:

template <>
void Vector<int>::swap(size_t index1, size_t index2) {
  // 对 int 类型元素进行特殊处理
}
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This avoids instantiating the genericswap() method multiple times, thus improving performance.

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