CS110 Lecture 10: Threads and Mutexes

Principles of Computer Systems

Winter 2021

Stanford University

Computer Science Department

Instructors: Chris Gregg and

                            Nick Troccoli

PDF of this presentation

CS110 Topic 3: How can we have concurrency within a single process?

Learning About Processes

Introduction to Threads

Mutexes and Condition Variables and Semaphores

More on Condition Variables and Semaphores

Multithreading Patterns

Lecture 9

Today

Lecture 11

Lecture 12

Today's Learning Goals

  • Discover some of the pitfalls of threads sharing the same virtual address space
  • Learn how locks can help us limit access to shared resources
  • Get practice using condition variables to wait for signals from other threads

Plan For Today

  • Recap: Threads in C++
  • Review of Mutexes
  • The Dining Philosophers Problem
    • Introduction to condition variables
    • The lock_guard
    • semaphores

Plan For Today

  • Recap: Threads in C++
  • Review of Mutexes
  • The Dining Philosophers Problem
    • Introduction to condition variables
    • The lock_guard

A thread is an independent execution sequence within a single process.

  • Most common: assign each thread to execute a single function in parallel
  • Each thread operates within the same process, so they share global data (!) (text, data, and heap segments)
  • They each have their own stack (e.g. for calls within a single thread)
  • Execution alternates between threads as it does for processes
  • Many similarities between threads and processes; in fact, threads are often called lightweight processes.

Threads

Processes:

  • isolate virtual address spaces (good: security and stability, bad: harder to share info)
  • can run external programs easily (fork-exec) (good)
  • harder to coordinate multiple tasks within the same program (bad)

Threads:

  • share virtual address space (bad: security and stability, good: easier to share info)
  • can't run external programs easily (bad)
  • easier to coordinate multiple tasks within the same program (good)

Threads vs. Processes

C++ thread

A thread object can be spawned to run the specified function with the given arguments.

thread myThread = thread(myFunc, arg1, arg2, ...);
  • myFunc: the function the thread should execute asynchronously
  • args: a list of arguments (any length, or none) to pass to the function upon execution
  • Once initialized with this constructor, the thread may execute at any time!

 

To pass objects by reference to a thread, use the ref() function:

void myFunc(int& x, int& y) {...}

thread myThread = thread(myFunc, ref(arg1), ref(arg2));

C++ thread

We can also initialize an array of threads as follows (note the loop by reference):

thread friends[5];
for (thread& currFriend : friends) {
    currFriend = thread(myFunc, arg1, arg2);
}   
// declare array of empty thread handles
thread friends[5];

// Spawn threads
for (size_t i = 0; i < 5; i++) {
	friends[i] = thread(myFunc, arg1, arg2); 
}

We can make an array of threads as follows:

C++ thread

For multiple threads, we must wait on a specific thread one at a time:

thread friends[5];
// spawn here
// now we wait for each to finish
for (size_t i = 0; i < 5; i++) {
	friends[i].join();
}

To wait on a thread to finish, use the .join() method:

thread myThread(myFunc, arg1, arg2);

... // do some work

// Wait for thread to finish (blocks)
myThread.join();

Thread Safety

A thread-safe function is one that will always execute correctly, even when called concurrently from multiple threads.

  • printf is thread-safe, but operator<< is not.  This means e.g. cout statements could get interleaved!
  • To avoid this, use ​oslock and osunlock (custom CS110 functions - #include "ostreamlock.h") around streams.  They ensure at most one thread has permission to write into a stream at any one time.
cout << oslock << "Hello, world!" << endl << osunlock;

Threads Share Memory

static void greeting(size_t& i) {
    cout << oslock << "Hello, world! I am thread " << i << endl << osunlock; 
}
    
static const size_t kNumFriends = 6;
int main(int argc, char *argv[]) {
  cout << "Let's hear from " << kNumFriends << " threads." << endl;  

  thread friends[kNumFriends]; // declare array of empty thread handles

  // Spawn threads
  for (size_t i = 0; i < kNumFriends; i++) {
      friends[i] = thread(greeting, ref(i)); 
  }   

  // Wait for threads
  for (size_t i = 0; i < kNumFriends; i++) {
     friends[i].join();    
  }

  cout << "Everyone's said hello!" << endl;
  return 0;
}
$ ./friends
Let's hear from 6 threads.
Hello, world! I am thread 2
Hello, world! I am thread 2
Hello, world! I am thread 3
Hello, world! I am thread 5
Hello, world! I am thread 5
Hello, world! I am thread 6
Everyone's said hello!

Output

for (size_t i = 0; i < kNumFriends; i++) {
    friends[i] = thread(greeting, ref(i)); 
}

_start

greeting

main

argc

argv

i

args

args

args

args

args

args

created thread stacks

main stack

Solution: pass a copy of i (not by reference) so it does not change.

Threads Share Memory

Plan For Today

  • Recap: Threads in C++
  • Review of Mutexes
  • The Dining Philosophers Problem
    • Introduction to condition variables
    • The lock_guard
    • semaphores

Mutex

https://www.flickr.com/photos/ofsmallthings/8220574255

A mutex is a variable type that represents something like a "locked door".

You can lock the door:

- if it's unlocked, you go through the door and lock it

- if it's locked, you ​wait for it to unlock first

 

If you most recently locked the door, you can unlock the door:

- door is now unlocked, another may go in now

  • A mutex is a type used to enforce mutual exclusion, i.e., a critical section
  • Mutexes are often called locks
    • To be very precise, mutexes are one kind of lock, there are others (read/write locks, reentrant locks, etc.), but we can just call them locks in this course, usually "lock" means "mutex"
  • When a thread locks a mutex
    • If the lock is unlocked the thread takes the lock and continues execution
    • If the lock is locked, the thread blocks and waits until the lock is unlocked
    • If multiple threads are waiting for a lock they all wait until lock is unlocked, one receives lock
  • When a thread unlocks a mutex
    • It continues normally; one waiting thread (if any) takes the lock and is scheduled to run
  • This is a subset of the C++ mutex abstraction: nicely simple!  How can we use this in our buggy program?
class mutex {
public:
  mutex();        // constructs the mutex to be in an unlocked state
  void lock();    // acquires the lock on the mutex, blocking until it's unlocked
  void unlock();  // releases the lock and wakes up another threads trying to lock it
};

Mutex - Mutual Exclusion

  • main instantiates a mutex, which it passes (by reference!) to invocations of process.
  • The process code uses this lock to protect remainingImages.
  • Note we need to unlock on line 5 -- in complex code forgetting this is an easy bug
static void process(size_t id, size_t& remainingImages, mutex& counterLock) {
  while (true) {
    counterLock.lock();
    if (remainingImages == 0) {
      counterLock.unlock(); 
      break;
    }
    processImage(remainingImages);
    remainingImages--;
    cout << oslock << "Thread#" << id << " processed an image (" << remainingImages 
     << " remain)." << endl << osunlock;
    counterLock.unlock();
  }
  cout << oslock << "Thread#" << id << " sees no remaining images and exits." 
  << endl << osunlock;
}

// Create single mutex in main, pass by reference

Critical Sections With Mutexes

  • The way we've set it up, only one thread agent can process an image at a time!
  • We can do better: serialize deciding which image to process and parallelize the actual processing
  • Keep your critical sections as small as possible!
static void process(size_t id, size_t& remainingImages, mutex& counterLock) {
  while (true) {
    size_t myImage;
    
    counterLock.lock();    // Start of critical section
    if (remainingImages == 0) {
      counterLock.unlock(); // Rather keep it here, easier to check
      break;
    } else {
      myImage = remainingImages;
      remainingImages--;
      counterLock.unlock(); // end of critical section

      processImage(myImage);
      cout << oslock << "Thread#" << id << " processed an image (" << remainingImages 
      << " remain)." << endl << osunlock;
    }
  }
  cout << oslock << "Thread#" << id << " sees no remaining images and exits." 
  << endl << osunlock;
}

Critical Sections Can Be Bottlenecks

Plan For Today

  • Recap: Threads in C++
  • Review of Mutexes
  • The Dining Philosophers Problem
    • Introduction to condition variables
    • The lock_guard
    • semaphores
  • The Dining Philosophers Problem
    • This is a canonical multithreading example used to illustrate the potential for deadlock and how to avoid it.
      • Five philosophers sit around a table, each in front of a big plate of spaghetti.
      • A single fork (the utensil, not the system call) is placed between neighboring philosophers.
        • Each philosopher comes to the table to think, eat, think, eat, think, and eat. That's three square meals of spaghetti after three extended think sessions.
        • Each philosopher keeps to themselves as they think. Sometime they think for a long time, and sometimes they barely think at all.
        • After each philosopher has thought for a while, they proceed to eat one of their three daily meals. In order to eat, they must grab hold of two forks—one on their left, then one on their right. With two forks in hand, they chow on spaghetti to nourish their big, philosophizing brain. When they're full, they put down the forks in the same order they picked them up and returns to thinking for a while.
    • The next two slides present the core of our first stab at the program that codes to this problem description. (The full program is right here.)

Lecture 10: Multithreading and Condition Variables

  • The Dining Philosophers Problem
    • The program models each of the forks as a mutex, and each philosopher either holds a fork or doesn't. By modeling the fork as a mutex, we can rely on mutex::lock to model a thread-safe fork grab and mutex::unlock to model a thread-safe fork release.
static void philosopher(size_t id, mutex& left, mutex& right) {
  for (size_t i = 0; i < 3; i++) {
    think(id);
    eat(id, left, right);
  }
}

int main(int argc, const char *argv[]) {
  mutex forks[5];
  thread philosophers[5];
  for (size_t i = 0; i < 5; i++) {
    mutex& left = forks[i], & right = forks[(i + 1) % 5];
    philosophers[i] = thread(philosopher, i, ref(left), ref(right));
  }
  for (thread& p: philosophers) p.join();
  return 0;
}

Lecture 10: Multithreading and Condition Variables

  • The Dining Philosophers Problem
    • The implementation of think is straightforward. It's designed to emulate the time a philosopher spends thinking without interacting with forks or other philosophers.
    • The implementation of eat is almost as straightforward, provided you understand the thread subroutine is being fed references to the two forks he needs to eat.
static void think(size_t id) {
  cout << oslock << id << " starts thinking." << endl << osunlock;
  sleep_for(getThinkTime());
  cout << oslock << id << " all done thinking. " << endl << osunlock;
}

static void eat(size_t id, mutex& left, mutex& right) {
  left.lock();
  right.lock();
  cout << oslock << id << " starts eating om nom nom nom." << endl << osunlock;
  sleep_for(getEatTime());
  cout << oslock << id << " all done eating." << endl << osunlock;
  left.unlock();
  right.unlock();
}

Lecture 10: Multithreading and Condition Variables

  • The program appears to work well (we'll run it several times), but it doesn't guard against this: each philosopher emerges from deep thought, successfully grabs the fork to their left, and is then forced off the processor because their time slice is up.
  • If all five philosopher threads are subjected to the same scheduling pattern, each would be stuck waiting for a second fork to become available.  That's a real deadlock threat.
  • Deadlock is more or less guaranteed if we insert a sleep_for call in between the two calls to lock, as we have in the version of eat presented below.
    • We should be able to insert a sleep_for call anywhere in a thread routine. If it surfaces a concurrency issue, then you have a larger problem to be solved.
static void eat(size_t id, mutex& left, mutex& right) {
  left.lock();
  sleep_for(5000);  // artificially force off the processor
  right.lock();
  cout << oslock << id << " starts eating om nom nom nom." << endl << osunlock;
  sleep_for(getEatTime());
  cout << oslock << id << " all done eating." << endl << osunlock;
  left.unlock();
  right.unlock();
}

Lecture 10: Multithreading and Condition Variables

  • When coding with threads, you need to ensure that:
    • there are no race conditions, even if they rarely cause problems, and
    • there's zero threat of deadlock, lest a subset of threads are forever starving for processor time.
  • mutexes are generally the solution to race conditions. We can use them to mark the boundaries of critical regions and limit the number of threads present within them to be at most one.
  • Deadlock can be programmatically prevented by implanting directives to limit the number of threads competing for a shared resource, like forks.
    • We could, for instance, recognize it's impossible for three philosophers to be eating at the same time. That means we could limit the number of philosophers who have permission to grab forks to a mere 2.
    • We could also argue it's okay to let four—though certainly not all five—philosophers grab forks, knowing that at least one will successfully grab both.
      • A decent preference: Impose a limit of four.
      • Rationale? Implant the minimal amount of bottlenecking needed to remove the threat of deadlock, and trust the thread manager to otherwise make good choices.

Lecture 10: Multithreading and Condition Variables

  • Here's the core of a program that limits the number of philosophers grabbing forks to four. (The full program can be found right here.)
    • We impose this limit by introducing the notion of a permission slip, or permit. Before grabbing forks, a philosopher must first acquire one of four permission slips.
    • These permission slips need to be acquired and released without race condition.
    • For now, we can model a permit using a counter—we'll call it permits—and a companion mutex—we'll call it permitsLock—that must be acquired before examining or changing permits.
int main(int argc, const char *argv[]) {
  size_t permits = 4;
  mutex forks[5], permitsLock;
  thread philosophers[5];
  for (size_t i = 0; i < 5; i++) {
    mutex& left = forks[i],
         & right = forks[(i + 1) % 5];
    philosophers[i] = 
        thread(philosopher, i, ref(left), ref(right), ref(permits), ref(permitsLock));
  }
  for (thread& p: philosophers) p.join();
  return 0;
}

Lecture 10: Multithreading and Condition Variables

  • The implementation of think is the same, so we don't present it again.
  • The implementation of eat, however, changes.
    • It accepts two additional references: one to the number of available permits, and a second to the mutex used to guard against simultaneous access to permits.
static void eat(size_t id, mutex& left, mutex& right, size_t& permits, mutex& permitsLock) {
  waitForPermission(permits, permitsLock); // on next slide
  left.lock(); right.lock();
  cout << oslock << id << " starts eating om nom nom nom." << endl << osunlock;
  sleep_for(getEatTime());
  cout << oslock << id << " all done eating." << endl << osunlock;
  grantPermission(permits, permitsLock); // on next slide
  left.unlock(); right.unlock();
}

static void philosopher(size_t id, mutex& left, mutex& right,
                        size_t& permits, mutex& permitsLock) {
  for (size_t i = 0; i < kNumMeals; i++) {
    think(id);
    eat(id, left, right, permits, permitsLock);
  }
}

Lecture 10: Multithreading and Condition Variables

  • The implementation of eat on the prior slide deck introduces calls to waitForPermission and grantPermission.
    • The implementation of grantPermission is certainly the easier of the two to understand: transactionally increment the number of permits by one.
    • The implementation of waitForPermission is less obvious. Because we don't know what else to do (yet!), we busy wait with short naps until the number of permits is positive. Once that happens, we consume a permit and then return.
static void waitForPermission(size_t& permits, mutex& permitsLock) {
  while (true) {
    permitsLock.lock();
    if (permits > 0) break;
    permitsLock.unlock();
    sleep_for(10);
  }
  permits--;
  permitsLock.unlock();
}

static void grantPermission(size_t& permits, mutex& permitsLock) {
  permitsLock.lock();
  permits++;
  permitsLock.unlock();
}

Lecture 10: Multithreading and Condition Variables

  • The second version of the program works, in the sense that it never deadlocks.
    • It does, however, suffer from busy waiting, which the systems programmer gospel says is verboten unless there are no other options.
  • A better solution? If a philosopher doesn't have permission to advance, then that thread should sleep until another thread sees reason to wake it up. In this example, another philosopher thread, after it increments permits within grantPermission, could notify the sleeping thread that a permit just became available.
  • Implementing this idea requires a more sophisticated concurrency directive that supports a different form of thread communication—one akin to the use of signals and sigsuspend to support communication between processes. Fortunately, C++ provides a standard directive called the condition_variable_any to do exactly this.
class condition_variable_any {
public:
   void wait(mutex& m);
   template <typename Pred> void wait(mutex& m, Pred pred);
   void notify_one();
   void notify_all();
};

Lecture 10: Multithreading and Condition Variables

  • Here's the main thread routine that introduces a condition_variable_any to support the notification model we'll use in place of busy waiting. (Full program: here)
    • The philosopher thread routine and the eat thread subroutine accept references to permits, cv, and m, because references to all three need to be passed on to waitForPermission and grantPermission.
    • We'll go with the shorter name m instead of permitsLock for reasons we'll get to soon. 
int main(int argc, const char *argv[]) {
  size_t permits = 4;
  mutex forks[5], m;
  condition_variable_any cv;
  thread philosophers[5];
  for (size_t i = 0; i < 5; i++) {
    mutex& left = forks[i], & right = forks[(i + 1) % 5];
    philosophers[i] = 
       thread(philosopher, i, ref(left), ref(right), ref(permits), ref(cv), ref(m));
  }
  for (thread& p: philosophers) p.join();
  return 0;
}

Lecture 10: Multithreading and Condition Variables

static void waitForPermission(size_t& permits, condition_variable_any& cv, mutex& m) {
  lock_guard<mutex> lg(m);
  while (permits == 0) cv.wait(m);
  permits--;
}

static void grantPermission(size_t& permits, condition_variable_any& cv, mutex& m) {
  lock_guard<mutex> lg(m);
  permits++;
  if (permits == 1) cv.notify_all();
}
  • The new implementations of waitForPermission and grantPermission are below:







     
    • The lock_guard is a convenience class whose constructor calls lock on the supplied mutex and whose destructor calls unlock on the same mutex. It's a convenience class used to ensure the lock on a mutex is released no matter how the function exits (early return, standard return at end, exception thrown, etc.)
    • grantPermission is a straightforward thread-safe increment, save for the fact that if permits just went from 0 to 1, it's possible other threads are waiting for a permit to become available. That's why the conditional call to cv.notify_all() is there.

Lecture 10: Multithreading and Condition Variables

static void waitForPermission(size_t& permits, condition_variable_any& cv, mutex& m) {
  lock_guard<mutex> lg(m);
  while (permits == 0) cv.wait(m);
  permits--;
}

static void grantPermission(size_t& permits, condition_variable_any& cv, mutex& m) {
  lock_guard<mutex> lg(m);
  permits++;
  if (permits == 1) cv.notify_all();
}
  • The new implementations of waitForPermission and grantPermission are below:







     
    • The implementation of waitForPermission will eventually grant a permit to the calling thread, though it may need to wait a while for one to become available.
      • If there aren't any permits, the thread is forced to sleep via cv.wait(m). The thread manager releases the lock on m just as it's putting the thread to sleep.
      • When cv is notified within grantPermission, the thread manager wakes the sleeping thread, but mandates it reacquire the lock on m (very much needed to properly reevaluate permits == 0) before returning from cv.wait(m).
      • Yes, waitForPermission requires a while loop instead an if test.  Why? It's possible the permit that just became available is immediately consumed by the thread that just returned it. Unlikely, but technically possible.

Lecture 10: Multithreading and Condition Variables

  • The Dining Philosophers Problem, continued
    • while loops around cv.wait(m) calls are so common that the
      condition_variable_any class exports a second, two-argument version of wait whose implementation is a while loop around the first. That second version looks like this:



       
    • It's a template method, because the second argument supplied via pred can be anything capable of standing in for a zero-argument, bool-returning function.
    • The first waitForPermissions can be rewritten to rely on this new version, as with:
template <Predicate pred>
void condition_variable_any::wait(mutex& m, Pred pred) {
  while (!pred()) wait(m);
}


static void waitForPermission(size_t& permits, condition_variable_any& cv, mutex& m) {
  lock_guard<mutex> lg(m);
  cv.wait(m, [&permits] { return permits > 0; });
  permits--;
}

Lecture 10: Multithreading and Condition Variables

  • Fundamentally, the size_t, condition_variable_any, and mutex are collectively working together to track a resource count—in this case, four permission slips.
    • They provide thread-safe increment in grantPermission and thread-safe decrement in waitForPermission.
    • They work to ensure that a thread blocked on zero permission slips goes to sleep indefinitely, and that it remains asleep until another thread returns one.
  • In our latest dining-philosopher example, we relied on these three variables to collectively manage a thread-safe accounting of four permission slips. However!
    • There is little about the implementation that requires the original number be four. Had we gone with 20 philosophers and and 19 permission slips, waitForPermission and grantPermission would still work as is.
    • The idea of maintaining a thread-safe, generalized counter is so useful that most programming languages include more generic support for it. That support normally comes under the name of a semaphore.
    • For reason that aren't entirely clear (though see here for a bit of context), standard C++ omits the semaphore from its standard libraries. But, it is easily built in terms of other supported constructs.

Lecture 10: Multithreading and Condition Variables

  • The semaphore constructor is so short that it's inlined right in the declaration of the semaphore class.
  • semaphore::wait is our generalization of waitForPermission.
void semaphore::wait() {
  lock_guard<mutex> lg(m);
  cv.wait(m, [this] { return value > 0; })
  value--;
}
  • Why does the capture clause include the this keyword?
    • Because the anonymous predicate function passed to cv.wait is just that—a regular function.  Since functions aren't normally entitled to examine the private state of an object, the capture clause includes this to effectively convert the bool-returning function into a bool-returning semaphore method.
  • semaphore::signal is our generalization of grantPermission.
void semaphore::signal() {
  lock_guard<mutex> lg(m);
  value++;
  if (value == 1) cv.notify_all();
}

Lecture 10: Multithreading and Condition Variables

  • Here's our final version of the dining-philosophers.
    • It strips out the exposed size_t, mutex, and condition_variable_any and replaces them with a single semaphore.
    • It updates the thread constructors to accept a single reference to that semaphore.
static void philosopher(size_t id, mutex& left, mutex& right, semaphore& permits) {
  for (size_t i = 0; i < 3; i++) {
    think(id);
    eat(id, left, right, permits);
  }
}

int main(int argc, const char *argv[]) {
  semaphore permits(4);
  mutex forks[5];
  thread philosophers[5];
  for (size_t i = 0; i < 5; i++) {
    mutex& left = forks[i], & right = forks[(i + 1) % 5];
    philosophers[i] = thread(philosopher, i, ref(left), ref(right), ref(permits));
  }
  for (thread& p: philosophers) p.join();
  return 0;
}

Lecture 10: Multithreading and Condition Variables

  • eat now relies on that semaphore to play the role previously played by waitForPermission and grantPermission.







  •  
    • We could switch the order of the last two lines, so that right.unlock() precedes
      left.unlock(). Is the switch a good idea? a bad one? or is it really just arbitrary?
    • One student suggested we use a mutex to bundle the calls to left.lock() and right.lock() into a critical region. Is this a solution to the deadlock problem?
    • We could lift the permits.signal() call up to appear in between right.lock() and the first cout statement. Is that valid? Why or why not?
static void eat(size_t id, mutex& left, mutex& right, semaphore& permits) {
  permits.wait();
  left.lock();
  right.lock();
  cout << oslock << id << " starts eating om nom nom nom." << endl << osunlock;
  sleep_for(getEatTime());
  cout << oslock << id << " all done eating." << endl << osunlock;
  permits.signal();
  left.unlock();
  right.unlock();
}

Lecture 10: Multithreading and Condition Variables

Recap

  • Recap: Threads in C++
  • Review of Mutexes
  • The Dining Philosophers Problem
    • Introduction to condition variables
    • The lock_guard
    • semaphores

Next time: more about concurrency directives

CS110 Lecture 10: Threads, Mutexes and Condition Variables (w21)

By Chris Gregg

Source: Nick Troccoli

CS110 Lecture 10: Threads, Mutexes and Condition Variables (w21)

Winter 2020

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