Máté Cserép
Eötvös Loránd University, Faculty of Informatics
May 2023, Budapest
Process
Thread
We will focus on multi thread programming.
Multithreading is just one damn thing after, before, or simultaneous with another.
Andrei Alexandrescu
Beyond the errors which can occur in single-threaded programs,
multithreaded environments are subject to additional errors:
Moreover testing and debugging of multithreaded programs are harder. Multithreaded programs are non-deterministic. Failures are often non-repeatable. Debugged code can produce very different results then non-debugged ones. Testing on single processor hardware may produce different results than testing on multiprocessor hardware.
int x, y;
// thread 1
x = 1;
y = 2;In C++11 this is undefined behaviour, in C++98/03 not even that.
// thread 2
std::cout << y << ", ";
std::cout << x << std::endl;int x, y;
std::mutex x_mutex, y_mutex;
// thread 1
x_mutex.lock();
x = 1;
x_mutex.unlock();
y_mutex.lock();
y = 2;
y_mutex.unlock();Workaround with mutexes:
// thread 2
y_mutex.lock();
std::cout << y << ", ";
y_mutex.unlock();
x_mutex.lock();
std::cout << x << std::endl;
x_mutex.unlock();std::atomic<int> x, y;
// thread 1
x.store(1);
y.store(2); Workaround with atomic:
// thread 2
std::cout << y.load() << ", ";
std::cout << x.load() << std::endl;namespace std
{
class thread
{
public:
typedef native_handle /* ... */;
typedef id /* ... */;
thread() noexcept; // does not represent a thread
thread(thread&& other) noexcept; // move constructor
~thread(); // if joinable() calls std::terminate()
template <typename Function, typename... Args> // copies args to thread local
explicit thread(Function&& f, Arg&&... args); // then execute f with args
thread(const thread&) = delete; // no copy
thread& operator=(thread&& other) noexcept; // move
void swap(thread& other); // swap
bool joinable() const; // thread object owns a physical thread
void join(); // blocks current thread until *this finish
void detach(); // separates physical thread from the thread object
std::thread::id get_id() const; // std::this_thread
static unsigned int hardware_concurrency(); // supported concurrent threads
native_handle_type native_handle(); // e.g. thread id
};
}void f(int i, const std::string& s);
std::thread t(f, 3, "Hello");Creates a new thread of execution with t, which calls f(3, "hello"), where arguments are copied (as is) into an internal storage (even if the function takes them as reference).
If an exception occurs, it will be thrown in the hosting thread.
class f
{
public:
f(int i = 0, std::string s = "") : _i(i), _s(s) { }
void operator()() const
{
// background activity
}
int _i;
std::string _s;
};
std::thread t(f()); // Most vexing parse (Scott Meyers: Effective STL)
std::thread t((f()); // OK
std::thread t((f(3, "Hello"))); // OKf can be any callable function, e.g. operator():
void f(int i, const std::string&)
{
std::cout << "Hello Concurrent World!" << std::endl;
}
int main()
{
int i = 3;
std::string s("Hello");
// Will copy both i and s
//std::thread t(f, i, s);
// We can prevent the copy by using reference wrapper
std::thread t(f, std::ref(i), std::ref(s));
// If the thread destructor runs and the thread is joinable, then
// std::system_error will be thrown.
// Use join() or detach() to avoid that.
t.join();
return 0;
}By default all arguments are copied by value, even if the function takes them as reference.
struct func
{
int& i;
func(int& i_) : i (i_) { }
void operator()()
{
for(unsigned int j = 0; j < 1000000; ++j)
{
do_something(i); // i may refer to a destroyed variable
}
}
};
int main()
{
int some_local_state = 0;
func my_func(some_local_state);
std::thread my_thread(my_func);
my_thread.detach(); // don't wait the thread to finish
return 0;
} // some_local_state is destroyed, but the thread is likely still running.
Still, there is possible to make wrong code (of course, this is C++).
Better to avoid pointers and references, or join().
class scoped_thread
{
std::thread t;
public:
explicit scoped_thread(std::thread t_): t(std::move(t_))
{
if(!t.joinable())
throw std::logic_error(“No thread”);
}
~scoped_thread()
{
t.join();
}
scoped_thread(scoped_thread const&)=delete;
scoped_thread& operator=(scoped_thread const&)=delete;
};
struct func;
void f()
{
int some_local_state;
scoped_thread t(std::thread(func(some_local_state)));
do_something_in_current_thread();
}Source: C++ Concurrency In Action, by Anthony Williams
Implementation can also be found in the Boost Library
<boost/thread/scoped_thread.hpp>
void f(int i, const std::string& s);
std::thread t(f, 3, "Hello");void f(int i, const std::string& s);
void bad(int some_param)
{
char buffer[1024];
sprintf(buffer, "%i", some_param);
std::thread t(f, 3, buffer);
t.detach();
}
void good(int some_param)
{
char buffer[1024];
sprintf(buffer,"%i",some_param);
std::thread t(f, 3, std::string(buffer));
t.detach();
}"Hello" is passed to f as const char * and converted to std::string in the new thread. This can lead to problems, e.g.:
void do_work(unsigned id);
int main()
{
std::vector<std::thread> threads;
for(unsigned i=0;i<20;++i)
{
threads.push_back(std::thread(do_work,i));
}
std::for_each(threads.begin(), threads.end(),
[](std::thread& t) { t.join(); }); // join all threads
std::for_each(threads.begin(), threads.end(), // alternative:
std::mem_fn(&std::thread::join)); // generates functor for function
return 0;
}sth::thread is compatible with the STL containers.
std::mutex m;
int sh; // shared data
void f()
{
/* ... */
m.lock();
// manipulate shared data:
sh += 1;
m.unlock();
/* ... */
}Mutex:
Recursive mutex:
std::recursive_mutex m;
int sh; // shared data
void f(int i)
{
/* ... */
m.lock();
// manipulate shared data:
sh += 1;
if (--i > 0) f(i);
m.unlock();
/* ... */
}std::timed_mutex m;
int sh; // shared data
void f()
{
/* ... */
if (m.try_lock_for(std::chrono::seconds(10))) {
// we got the mutex, manipulate shared data:
sh += 1;
m.unlock();
}
else {
// we didn't get the mutex; do something else
}
}
void g()
{
/* ... */
if (m.try_lock_until(midnight)) {
// we got the mutex, manipulate shared data:
sh+=1;
m.unlock();
}
else {
// we didn't get the mutex; do something else
}
}Timed mutex:
std::list<int> l;
std::mutex m;
void add_to_list(int value);
{
// lock acquired - with RAII style lock management
std::lock_guard<std::mutex> guard(m);
l.push_back(value);
} // lock releasedLocks support the Resource Allocation Is Initialization (RAII) idiom.
Pointers or references pointing out from the guarded area can be an issue!
template <class T>
bool operator<(const T& lhs, const X& rhs)
{
if (&lhs == &rhs)
return false;
lhs.m.lock(); rhs.m.lock();
bool result = lhs.data < rhs.data;
lhs.m.unlock(); rhs.m.unlock();
return result;
}The code below can result in a deadlock when a < b and b < a are simultaneously evaluated on 2 threads.
Avoid deadlocks
template <class T>
bool operator<(T const& lhs, X const& rhs)
{
if (&lhs == &rhs)
return false;
// std::lock - locks two or more mutexes
std::lock(lhs.m, rhs.m);
// std::adopt_lock - assume the calling thread already has ownership
std::lock_guard<std::mutex> lock_lhs(lhs.m, std::adopt_lock);
std::lock_guard<std::mutex> lock_rhs(rhs.m, std::adopt_lock);
return lhs.data < rhs.data;
}
A correct solution to avoid deadlock:
With the lock guards, mutexes are released with RAII.
template <class T>
bool operator<(T const& lhs, X const& rhs)
{
if (&lhs == &rhs )
return false;
// std::unique_locks constructed with defer_lock can be locked
// manually, by using lock() on the lock object ...
std::unique_lock<std::mutex> lock_lhs(lhs.m, std::defer_lock);
std::unique_lock<std::mutex> lock_rhs(rhs.m, std::defer_lock);
// lock_lhs.owns_lock() now false
// ... or passing to std::lock
std::lock(lock_lhs, lock_rhs); // designed to avoid dead-lock
// also there is an unlock() member function
// lock_lhs.owns_lock() now true
return lhs.data < rhs.data;
}Another correct solution with different approach:
std::unique_lock can be locked and unlocked.
(It is also moveable, but not copyable, but that is not a factor here.)
template <class T>
bool operator<(T const& lhs, X const& rhs)
{
if (&lhs == &rhs )
return false;
// designed to avoid dead-lock
std::scoped_lock lock(lhs.m, rhs.m);
return lhs.data < rhs.data;
}C++17 simplifies the problem with the introduction of scoped_lock, specifically designed for locking (and releasing) multiple mutexes and the same time in RAII style:
template <typename T>
class MySingleton
{
public:
std::shared_ptr<T> instance()
{
std::unique_lock<std::mutex> lock(resource_mutex);
if (!resource_ptr)
resource_ptr.reset(new T(/* ... */));
lock.unlock();
return resource_ptr;
}
private:
std::shared_ptr<T> resource_ptr;
mutable std::mutex resource_mutex;
};Problem: while the problematic race condition is connected only to the initialization of the Singleton instance, the critical section is executed for every calls of the instance() method. Such an excessive usage of the locking mechanism may cause serious overhead which could not be acceptable.
template <typename T>
class MySingleton
{
public:
std::shared_ptr<T> instance()
{
if (!resource_ptr) // 1
{
std::unique_lock<std::mutex> lock(resource_mutex);
if (!resource_ptr)
resource_ptr.reset(new T(/* ... */)); // 2
lock.unlock();
}
return resource_ptr;
}
private:
std::shared_ptr<T> resource_ptr;
mutable std::mutex resource_mutex;
};Problem: load in (1) and store in (2) is not synchronized.
This can lead to a bug with non-atomic pointer or integral assignment semantics; or if an overly-aggressive compiler optimizes resource_ptr (e.g. storing it in a register).
Double-Checked Locking Pattern
template <typename T>
class MySingleton
{
public:
std::shared_ptr<T> instance()
{
std::call_once(resource_init_flag, init_resource);
return resource_ptr;
}
private:
void init_resource()
{
resource_ptr.reset(new T(/* ... */));
}
std::shared_ptr<T> resource_ptr;
std::once resource_init_flag; // can't be moved or copied
};std::call_once is guaranteed to execute its callable parameter exactly once, even if called from several threads.
class MySingleton;
MySingleton& MySingletonInstance()
{
static MySingleton _instance;
return _instance;
}
C++11 guarantees that this is thread safe!
std::mutex my_mutex;
std::queue<data_t> my_queue;
std::conditional_variable data_cond; // conditional variable
void producer() {
while (more_data_to_produce())
{
const data_t data = produce_data();
std::lock_guard<std::mutex> prod_lock(my_mutex); // guard the push
my_queue.push(data);
data_cond.notify_one(); // notify the waiting thread to evaluate cond.
}
}
void consumer() {
while (true)
{
std::unique_lock<std::mutex> cons_lock(my_mutex); // not lock_guard
data_cond.wait(cons_lock, // returns if lamdba returns true
[&my_queue]{return !my_queue.empty();}); // else unlocks and waits
data_t data = my_queue.front(); // lock is hold here to protect pop...
my_queue.pop();
cons_lock.unlock(); // ... until here
consume_data(data);
}
}Classical producer-consumer example:
int f(int);
void do_other_stuff();
int main()
{
std::future<int> the_answer = std::async(f, 1);
do_other_stuff();
std::cout<< "The answer is " << the_answer.get() << std::endl;
return 0;
}The std::async() executes the task either in a new thread or on get().
// starts in a new thread
auto fut1 = std::async(std::launch::async, f, 1);
// run in the same thread on wait() or get()
auto fut2 = std::async(std::launch::deferred, f, 2);
// default: implementation chooses
auto fut3 = std::async(std::launch::deferred | std::launch::async, f, 3);
// default: implementation chooses
auto fut4 = std::async(f, 4);If no wait() or get() is called, then the task may not be executed at all.
double square_root(double x)
{
if (x < 0)
{
throw std::out_of_range("x is negative");
}
return sqrt(x);
}
int main()
{
std::future<double> fut = std::async(square_root, -1);
double res = fut.get(); // f becomes ready on exception and rethrows
return 0;
} double long_calculation(int n)
{
/* ... */
}
int main()
{
std::async(std::launch::async, long_calculation, 42); // ~future blocks
std::async(std::launch::async, long_calculation, 100); // ~future blocks
} int main()
{
std::future<double> fut1 = std::async(std::launch::async, long_calculation, 42);
// no blocking
std::future<double> fut2 = std::async(std::launch::async, long_calculation, 100);
// no blocking
} Keep in mind that the futures has a special shared state, which demands that future::~future blocks.
For real asynchronous you need to keep the returned future:
A promise is a tool for passing the return value (or exception) from a thread executing a function to the thread that consumes the result using future.
void asyncFun(std::promise<int> myPromise)
{
int result;
try
{
// calculate the result
myPromise.set_value(result);
}
catch (...)
{
myPromise.set_exception(std::current_exception());
}
}int main()
{
std::promise<int> intPromise;
std::future<int> intFuture = intPromise.getFuture();
std::thread t(asyncFun, std::move(intPromise));
// do other stuff here, while asyncFun is working
int result = intFuture.get(); // may throw exception
return 0;
}void asyncFun(std::promise<int> myPromise)
{
int result;
try
{
// calculate the result
myPromise.set_value(result);
}
catch (...)
{
myPromise.set_exception(std::current_exception());
}
}double square_root(double x)
{
if ( x < 0 )
{
throw std::out_of_range("x<0");
}
return sqrt(x);
}
int main()
{
double x = 4.0;
std::packaged_task<double(double)> tsk(square_root);
std::future<double> fut = tsk.get_future(); // future will be ready when task completes
std::thread t(std::move(tsk), x); // make sure, task starts immediately
// on different thread
// thread can be joined, detached
double res = fut.get(); // using the future
return 0;
}A higher level tool than promises.
template <typename> class my_task;
template <typename R, typename ...Args>
class my_task<R(Args...)>
{
std::function<R(Args...)> fn;
std::promise<R> pr;
public:
template <typename ...Ts>
explicit my_task(Ts&&... ts) : fn(std::forward<Ts>(ts)...) { }
template <typename ...Ts>
void operator()(Ts&&... ts)
{
pr.set_value(fn(std::forward<Ts>(ts)...));
}
std::future<R> get_future() { return pr.get_future(); }
// disable copy, default move
};In the end a std::packaged_task is just a lower level feature for implementing std::async (which is why it can do more than std::async if used together with other lower level stuff, like std::thread).
Simply spoken a std::packaged_task is a std::function linked to a std::future and std::async wraps and calls a std::packaged_task (possibly in a different thread).
C++17 brings us parallel algorithms, so the well known STL algorithms (std::find_if, std::for_each, std::sort, etc.) get a support for parallel (or vectorized) execution.
vector<int> v = { /* ... */ };
// standard sequential sort
std::sort(v.begin(), v.end());
// sequential execution
std::sort(std::parallel::seq, v.begin(), v.end());
// permitting parallel execution
std::sort(std::parallel::par, v.begin(), v.end());
// permitting vectorized execution (only since C++20)
std::sort(std::parallel::unseq, v.begin(), v.end());
// permitting parallel and vectorized execution
std::sort(std::parallel::par_unseq, v.begin(), v.end());What is vectorized (or unsequenced) execution?
Parallel STL is only implemented in modern compilers, so keep in mind where you can use this new feature.
Support is not necessarily complete immediately, e.g. MSVC only implements the vectorized execution policy since MSVC 19.28 (VS 2019 16.8+)
Follow current state at:
https://en.cppreference.com/w/cpp/compiler_support
Look for "Parallel algorithms and execution policies".
Everybody who learns concurrency thinks they understand it, ends up finding mysterious races they thought weren't possible, and discovers that they didn't actually understand it yet after all.
Herb Sutter
Chair of the ISO C++ standards committee, Microsoft
Atomic data types: bool, char, byte, sbyte, short, ushort, uint, int, float, and reference types.
Non-atomic data types: long, ulong, double, decimal, etc.
There is no guarantee of atomic read-modify-write, such as in the case of increment or decrement.
class SomeType { /* ... */ }
public static Program {
public static void Main(string[] args) {
int x = 41;
Interlocked.Increment(ref x); // increment x
SomeType y = new SomeType();
SomeType z = new SomeType();
// ...
Interlocked.Exchange(ref y, z); // replace y with z
}
Basic atomicity can be achieved through the methods of the Interlocked class:
public Stack<T>
{
private Mutex mutex;
private IList<T> values;
public Stack()
{
mutex = new Mutex();
values = new List<T>();
}
public void Push(T item);
{
mutex.WaitOne();
values.Add(item); // critical section
mutex.ReleaseMutex();
}
}
Can also wait until a timeout reached:
mutex.WaitOne(Int32) and mutex.WaitOne(TimeSpan)
public Stack<T>
{
private Semaphore sem;
private IList<T> values;
public Stack()
{
sem = new Semaphore();
values = new List<T>();
}
public void Push(T item);
{
sem.WaitOne();
values.Add(item); // critical section
sem.Release();
}
}
Can specify the number of initial entries (ownership) and the maximum number of concurrent entries:
Semaphore sem = new Semaphore(0, 3);public Stack<T>
{
private IList<T> values;
public Stack()
{
values = new List<T>();
}
public void Push(T item);
{
Monitor.Enter(values);
values.Add(item); // critical section
Monitor.Exit(values);
}
}
public void Push(T item);
{
lock(values)
{
values.Add(item); // critical section
}
}
Same as using the lock statement:
Mutex:
Semaphore:
Monitor:
Thread-safe, mutually exclusive collections are part of the .NET Standard Library, under the System.Collections.Concurrent namespace
IDictionary<String, Object> dictionary =
new ConcurrentDictionary<String, Object>();class Program {
public static void DoWork() {
Console.WriteLine("Child thread starts");
Console.WriteLine("Child thread goes to sleep");
Thread.Sleep(5000); // the thread is paused for 5000 milliseconds
Console.WriteLine("Child thread resumes and finishes");
}
static void Main(string[] args) {
ThreadStart childJob = new ThreadStart(DoWork);
Console.WriteLine("Main thread starts");
Thread childThread = new Thread(childJob);
childThread.Start();
Console.WriteLine("Main thread waiting");
childThread.Join();
Console.WriteLine("Main thread finishes");
}
}class Program {
public static void DoWork(object obj) {
Console.WriteLine("Child thread starts");
if (obj is String)
Console.WriteLine(obj as String);
else
throw new ArgumentException("Parameter is not a string.", nameof(obj));
Console.WriteLine("Child thread goes to sleep");
Thread.Sleep(5000); // the thread is paused for 5000 milliseconds
Console.WriteLine("Child thread resumes and finishes");
}
static void Main(string[] args) {
ParameterizedThreadStart childJob = new ParameterizedThreadStart(DoWork);
Console.WriteLine("Main thread starts");
Thread childThread = new Thread(childJob);
childThread.Start("Message from Main");
Console.WriteLine("Main thread waiting");
childThread.Join();
Console.WriteLine("Main thread finishes");
}
}Problems with plain Thread objects:
private Int32 Compute(){ /* ... */ }
// calculation which produces a result
private void RunCompute() {
Int32 result = Task.Run(() => Compute()).Result;
// execute task and wait for the result
// ...
}private Int32 Compute(){ /* ... */ }
// calculation which produces a result
private void RunCompute() {
Task<Int32> myTask = new Task<Int32>(() => Compute());
// create a task with the job given
myTask.Start(); // start the task
// ...
Int32 result = myTask.Result;
// wait for the result
// ...
}class Program {
public static int Add(int a, int b) {
Console.WriteLine("Child thread starts");
int result = a + b;
Console.WriteLine("Child thread goes to sleep");
Thread.Sleep(5000); // the thread is paused for 5000 milliseconds
Console.WriteLine("Child thread resumes and finishes");
return result;
}
public static void Main(string[] args) {
int x = 30;
int y = 12;
Task<int> task = new Task<int>(() => Add(x, y));
Console.WriteLine("Main thread starts");
task.Start();
Console.WriteLine("Main thread waiting");
int sum = task.Result; // blocks until result is ready
// alternative: task.Wait() and its overloads
Console.WriteLine("Main thread finishes, sum = {0}", sum);
}
}public static void Main(string[] args) {
Console.WriteLine("Main thread starts");
Task<int> taskA = DoWorkAsync(42);
Task<int> taskB = DoWorkAsync(100);
Console.WriteLine("Main thread waiting");
try {
Task.WaitAll(new Task[] { taskA, taskB });
// taskA.Result and taskB.Result are available at this point
}
catch (AggregateException ae) {
foreach (var e in ae.InnerExceptions) {
// handle exception ...
}
}
Console.WriteLine("Main thread finishes");
}Unhandled exceptions thrown by user code that is running inside a task are propagated back to the calling thread.
Multiple exception can be thrown (e.g. when on waiting multiple child tasks), so the Task infrastructure wraps them in an AggregateException instance.
class Program {
public static int Add(int a, int b) {
/* ... */
}
public static async Task<int> AddAsync(int a, int b)
{
int result = await Task.Run(() => Add(a, b));
Console.WriteLine("Result computed = {0}", result);
return result;
}
public static void Main(string[] args) {
int x = 30;
int y = 12;
Console.WriteLine("Main thread starts");
Task<int> task = AddAsync(x, y);
Console.WriteLine("Main thread waiting");
int sum = task.Result;
Console.WriteLine("Main thread finishes, sum = {0}", sum);
}
}Since .NET 4.5 methods of standard library which should be run as a background tasks are available as asynchronous operations.
StreamReader reader = new StreamReader("somefile.txt");
String firstLine = await reader.ReadLineAsync();Threads can be terminated through the Abort method unconditionally, which is considered an obsolete solution.
class Program {
public static void Main(string[] args) {
// ...
CancellationTokenSource source = new CancellationTokenSource(); // token source
CancellationToken token = source.Token; // token
Task.Run(() => {
// ...
if (token.IsCancellationRequested)
// if requested
return; // we cancel the execution
// ...
}, token); // pass the cancellation token
// ...
}
}class Program {
public static void Main(string[] args) {
// ...
TaskScheduler scheduler = TaskScheduler.FromCurrentSynchronizationContext();
// scheduler for synchronization
Task.Factory.StartNew(() => { ... }, ..., ..., scheduler)
// the task will be executed synchronously
Task.Factory.StartNew(() => { ... })
.ContinueWith(() => { label.Text = "Ready." }, scheduler);
// the task is executed asynchronously,
// then executes a synchronous operation
// to provide a thread-safe way to access the UI
// ...
}
}