How to balance performance and maintainability of C++ programs?

To balance performance and maintainability in C programs, you can use the following tips: Choose the right tools: such as modern memory management libraries, data structures, and template libraries. Optimize your code: Improve performance by inlining functions, using pointers, and avoiding virtual functions. Stay readable and organized: write comments, follow naming conventions, and break up large functions.

How to balance the performance and maintainability of C programs

In C, balancing performance and maintainability is crucial . Here are some practical tips for achieving this:

Choosing the right tools

• Memory Management Libraries: Modern Memory Management Libraries (like TBB) can significantly improve performance.
• Data structures: Use data structures suitable for specific tasks (such as unordered maps, hash tables).
• Template library: Use the Standard Template Library (STL) and third-party template libraries to improve readability and reusability.

Optimize code

• Inline functions: Mark critical functions as inline to avoid function call overhead.
• Pointers instead of references: Using pointers instead of references can improve performance, but may also hurt maintainability.
• Avoid virtual functions: Virtual functions are expensive to call, so they should be used when necessary.

Keep it readable and organized

• Write documentation comments: Use comments to explain code intent and usage .
• Follow naming conventions: Use a consistent naming convention to improve readability.
• Broken up large functions: Improve maintainability by breaking large functions into smaller manageable chunks.

Practical case: Optimizing hash table lookup performance

The following is a practical case for optimizing hash table lookup performance:

// 使用标准哈希表
unordered_map<int, int> hash_table;

// 使用 TBB 并行哈希表
tbb::concurrent_unordered_map<int, int> parallel_hash_table;

int main() {
  // 插入数据
  for (int i = 0; i < 1000000; ++i) {
    hash_table[i] = i;
    parallel_hash_table[i] = i;
  }

  // 查找时间比较
  auto start = std::chrono::high_resolution_clock::now();
  for (int i = 0; i < 100000; ++i) {
    auto it = hash_table.find(i);
    if (it == hash_table.end()) { /* 处理找不到的情况 */ }
  }
  auto end = std::chrono::high_resolution_clock::now();
  auto duration = std::chrono::duration_cast<std::chrono::duration<double>>(end - start);

  // 并行版本的查找
  start = std::chrono::high_resolution_clock::now();
  for (int i = 0; i < 100000; ++i) {
    auto it = parallel_hash_table.parallel_find(i);
    if (it == parallel_hash_table.end()) { /* 处理找不到的情况 */ }
  }
  end = std::chrono::high_resolution_clock::now();
  auto parallel_duration = std::chrono::duration_cast<std::chrono::duration<double>>(end - start);

  std::cout << "标准哈希表查找时间： " << duration.count() << " 秒" << std::endl;
  std::cout << "并行哈希表查找时间： " << parallel_duration.count() << " 秒" << std::endl;

  return 0;
}

In In the above example, TBB parallel hash tables significantly improve lookup performance while maintaining high maintainability.

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