Introduction to multithreading in C++ — what you need to know at the start

Introduction to multithreading in C++ — what you need to know at the start

Digital illustration of a futuristic circuit board with glowing elements on a dark background

Multithreading is one of those C++ tools that can either dramatically speed up your program or turn it into a source of complex, hard-to-reproduce bugs. By 2025, multithreading has become even more accessible thanks to C++11–C++20, but the core principles and pitfalls remain the same.

This article is for those who are just planning their first steps into multithreaded programming in C++. We won’t jump straight into writing complex thread pools or lock-free queues — first, we’ll cover the fundamentals you need to avoid critical mistakes.

1. Why multithreading is essential right now

Modern processors have anywhere from 4 to 128+ cores. If your program uses only one thread — you are literally wasting 75–95% of the available computing power. Multithreading enables:

  • parallel data processing (e.g., image processing, machine learning, servers)
  • background tasks (file downloads, network requests)
  • acceleration of computations on multi-core hardware

But there is a cost: code becomes more complex, and you introduce race conditions, deadlocks, and data races.

2. Basic building blocks (C++11+)

std::thread — the main class for creating a thread

#include <thread>
#include <iostream>

void sayHello() {
    std::cout << "Hello from thread " << std::this_thread::get_id() << "\n";
}

int main() {
    std::thread t(sayHello);
    t.join();  // must wait for completion
    return 0;
}

Important notes:

  • If you do not call join() or detach() — the program will terminate with an error (terminate called without an active exception)
  • detach() detaches the thread — it runs independently (rarely used)

Passing parameters:

void printNumber(int n) {
    std::cout << "Number: " << n << "\n";
}

std::thread t(printNumber, 42);

3. The most common beginner mistake — race condition 

int counter = 0;

void increment() {
    for (int i = 0; i < 100000; ++i) {
        counter++;  // DANGEROUS!
    }
}

int main() {
    std::thread t1(increment);
    std::thread t2(increment);
    t1.join();
    t2.join();
    std::cout << "Counter: " << counter << "\n";  // almost never 200000
}

The result will almost always be less than 200000 due to a race condition.

4. First line of defense — mutex (C++11)

#include <mutex>

std::mutex mtx;
int counter = 0;

void increment() {
    for (int i = 0; i < 100000; ++i) {
        std::lock_guard<std::mutex> lock(mtx);  // automatically unlocks on scope exit
        counter++;
    }
}

Now counter will always be exactly 200000.

Alternative — std::atomic (for simple types):

std::atomic<int> counter{0};

void increment() {
    for (int i = 0; i < 100000; ++i) {
        counter.fetch_add(1, std::memory_order_relaxed);
    }
}

5. What you need to know before your first real multithreaded project

  • Always call join() or detach() on every std::thread
  • Use std::lock_guard or std::unique_lock — never hold a mutex manually
  • For simple counters — std::atomic is faster than mutex
  • Avoid global variables — pass data via parameters or std::future
  • Start with std::jthread (C++20) — it automatically joins in its destructor
#include <thread>  // C++20

std::jthread jt([]{
    // this thread automatically finishes when leaving scope
});

6. Short roadmap for your first steps in multithreading

  1. Write a simple program with 2–3 threads that have no shared data
  2. Add a shared variable → observe the race condition
  3. Protect it with a mutex → verify correctness
  4. Try std::atomic for simple counters
  5. Move on to std::async and std::future for asynchronous computations

This is the foundation. Without it, you should not attempt thread pools, condition variables, or lock-free structures.

Multithreading is a powerful tool. But first, learn not to shoot yourself in the foot.

Back to blog