A multithreaded program contains two or more parts that can run concurrently. ... Each part of such a program is called a thread, and each thread defines a separate path of execution. C++ does not contain any built-in support for multithreaded applications.
A thread can be created in several ways:
Using a function pointer
Using a functor
Using a lambda function
These methods are very similar with minor differences. I explain each method and their differences next.
Using a function pointer
Consider the following function which takes a vector reference v, a reference to the result acm, and two indices in the vector v. The function adds all elements between beginIndex and endIndex.
void accumulator_function2(const std::vector<int> &v,
unsigned long long &acm,
unsigned int beginIndex,
unsigned int endIndex)
{
acm = 0;
for (unsigned int i = beginIndex; i < endIndex; ++i)
{
acm += v[i];
}
}A function calculating the sum of all elements between beginIndex and endIndex in a vector v
Now lets say you want to partition the vector in two sections and calculate the total sum of each section in a separate thread t1 and t2 :
//Pointer to function
{
unsigned long long acm1 = 0;
unsigned long long acm2 = 0;
std::thread t1(accumulator_function2, std::ref(v),
std::ref(acm1), 0, v.size() / 2);
std::thread t2(accumulator_function2, std::ref(v),
std::ref(acm2), v.size() / 2, v.size());
t1.join();
t2.join();
std::cout << "acm1: " << acm1 << endl;
std::cout << "acm2: " << acm2 << endl;
std::cout << "acm1 + acm2: " << acm1 + acm2 << endl;
}Creating threads using function pointers
What do you need to take away?
std::thread creates a new thread. The first parameter is the name of the function pointer accumulator_function2. Therefore, each thread will execute this function.
The rest of the parameters passed to std::thread constructor are the parameters that we need to pass to accumulator_function2.
Important: All parameters passed to accumulator_function2 are passed by value unless you wrap them in std::ref. That’s why we wrapped v , acm1 , and acm2 in std::ref.
Threads created by std::thread do not have return values. If you want to return something, you should store it in one of the parameters passed by reference, i.e. acm .
Each thread starts as soon as it gets created.
We use join() function to wait for a thread to finish
Using Functors
You can do exactly the same thing using functors. The following is the code that uses a functor:
class CAccumulatorFunctor3
{
public:
void operator()(const std::vector<int> &v,
unsigned int beginIndex, unsigned int endIndex)
{ _
acm = 0;
for (unsigned int i = beginIndex; i < endIndex; ++i)
{
_acm += v[i];
}
}
unsigned long long _acm;
};Functor Definition
And the code that creates the threads is:
//Creating Thread using Functor
{
CAccumulatorFunctor3 accumulator1 = CAccumulatorFunctor3();
CAccumulatorFunctor3 accumulator2 = CAccumulatorFunctor3();
std::thread t1(std::ref(accumulator1),
std::ref(v), 0, v.size() / 2);
std::thread t2(std::ref(accumulator2),
std::ref(v), v.size() / 2, v.size());
t1.join();
t2.join();
std::cout << "acm1: " << accumulator1._acm << endl;
std::cout << "acm2: " << accumulator2._acm << endl;
std::cout << "accumulator1._acm + accumulator2._acm : " <<
accumulator1._acm + accumulator2._acm << endl;
}Creating threads using functors
What do you need to take away?
Everything is very similar to function pointer, except that:
The first parameter is the functor object.
Instead of passing a reference to the functor to store the result, we can store its return value in a member variable inside the functor, i.e. in _acm.
Using Lambda Functions
As the third alternative we can define each thread in a lambda function as shown below:
{
unsignedlonglong acm1 = 0;
unsignedlonglong acm2 = 0;
std::thread t1([&acm1, &v]
{
for (unsignedint i = 0; i < v.size() / 2; ++i)
{
acm1 += v[i];
}
});
std::thread t2([&acm2, &v]
{
for (unsignedint i = v.size() / 2; i < v.size(); ++i)
{
acm2 += v[i];
}
});
t1.join();
t2.join();
std::cout << "acm1: " << acm1 << endl;
std::cout << "acm2: " << acm2 << endl;
std::cout << "acm1 + acm2: " << acm1 + acm2 << endl;
}Creating threads using lambda functions
Again, everything is very similar to function pointer, except that:
As an alternative to pass a parameter, we can pass references to lambda functions using lambda capture.
Tasks, Futures, and Promises
As an alternative to std::thread, you can use tasks.
Tasks work very similar to threads, but the main difference is that they can return a value. So, you can remember them as a more abstract way of defining your threads and use them when the threads return a value.
Below is the same example written using tasks:
#include<future>
//Tasks, Future, and Promises
{
auto f1 = [](std::vector<int> &v,
unsignedint left,
unsignedint right)
{
unsignedlonglong acm = 0;
for (unsignedint i = left; i < right; ++i)
{
acm += v[i];
}
return acm;
};
auto t1 = std::async(f1, std::ref(v),
0, v.size() / 2);
auto t2 = std::async(f1, std::ref(v),
v.size() / 2, v.size());
//You can do other things here!
unsignedlonglong acm1 = t1.get();
unsignedlonglong acm2 = t2.get();
std::cout << "acm1: " << acm1 << endl;
std::cout << "acm2: " << acm2 << endl;
std::cout << "acm1 + acm2: " << acm1 + acm2 << endl;
}What do you need to take away?
Tasks are defined and created using std::async , (instead of threads that are created using std::thread)
The returned value from std::async is called a std::future. Don’t get scared by its name. It just means t1 and t2 are variables whose value will be assigned to in the future. We get their values by calling t1.get() and t2.get()
If the future values are not ready, upon calling get() the main thread blocks until the future value becomes ready (similar to join() ).
Notice that the function that we passed to std::async returns a value. This value is passed through a type called std::promise. Again, don’t get scared by its name. For the most part, you don’t need to know details of std::promiseor define any variable of type std::promise. The C++ library does that behind the scenes.
Each task by default starts as soon as it is created (there is a way to change this which I don’t cover).
Summary of Creating Threads
There you have it. Creating threads is as simple as what I explained above. You can either use std::thread:
Use function pointers
Use functors
Use lambda functions
Or you can use std::async to create a task and get the return values in a std::future. Tasks can get also use a function pointer, a functor, or a lambda function.
In short, threads should be careful when they read/write into shared memory and resources (such as files) to avoid race conditions.
C++14 provides several constructs to synchronize threads to avoid such race conditions.
Using Mutex, lock,() and unlock() (Not recommended)
The following code shows how we create a critical section such that each thread accesses std::cout exclusively:
std::mutex g_display_mutex;
thread_function()
{
g_display_mutex.lock();
std::thread::id this_id = std::this_thread::get_id();
std::cout << "My thread id is: " << this_id << endl;
g_display_mutex.unlock();
}What do you need to take away?
A mutex is created std::mutex
A critical section (i.e. guaranteed to be run only by a single thread at each time) is created using lock()
The critical section ends upon calling unlock()
Each thread waits at lock() and only enters the critical section if no other thread is inside that section.
While the above method works, it is not recommended because:
It is not exception safe: if the code before lock generates an exception, unlock()will not be executed, and we never release the mutex which might cause deadlock
We always have to be careful not to forget to call unlock()
Using std::lock_guard (recommended)
Don’t get scared by its name lock_guard. It’s just a more abstract way of creating critical sections.
Below is the same critical section using lock_guard.
std::mutex g_display_mutex;
thread_function()
{
std::lock_guard<std::mutex> guard(g_display_mutex);
std::thread::id this_id = std::this_thread::get_id();
std::cout << "From thread " << this_id << endl;
}critical section using lock_guard
What do you need to take away?
The code coming after std::lock_guard creation is automatically locked. No need for explicit lock() and unlock() function calls.
The critical section automatically ends when std::lock_guard goes out of scope. This makes it exception safe, and also we don’t need to remember to call unlock()
lock_guard still requires using a variable of type std::mutex in its constructor.
How Many Threads Should We Create?
You can create as many threads as you want, but it would probably be pointless if the number of active threads is more than the number of available CPU cores.
In order to get the maximum number of cores you can call: std::thread::hardware_concurrency() as shown below:
{
unsigned int c = std::thread::hardware_concurrency();
std::cout << " number of cores: " << c << endl;;
}What I Didn’t Cover
I covered most of what you need to create threads. There are several other details that are less common which I don’t include here, but you can study them on your own:
std::move
details of std::promise
std::packaged_task
Conditional variables
Hope this helps you learning C++ multi threading quickly.
Source: Medium
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