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Semaphores are Surprisingly Versatile

Semaphores are Surprisingly Versatile

2023-01-25 09:19:10

In multithreaded programming, it’s essential to make threads wait. They need to anticipate unique entry to a useful resource. They need to wait when there’s no work accessible. One option to make threads wait – and put them to sleep contained in the kernel, in order that they not take any CPU time – is with a semaphore.

I used to suppose semaphores had been unusual and old school. They had been invented by Edsger Dijkstra back in the early 1960s, earlier than anybody had completed a lot multithreaded programming, or a lot programming in any respect, for that matter. I knew {that a} semaphore may preserve monitor of obtainable items of a useful resource, or operate as a clunky type of mutex, however that gave the impression to be about it.

My opinion modified as soon as I spotted that, utilizing solely semaphores and atomic operations, it’s potential to implement the entire following primitives:

  1. A Light-weight Mutex
  2. A Light-weight Auto-Reset Occasion Object
  3. A Light-weight Learn-Write Lock
  4. One other Resolution to the Eating Philosophers Downside
  5. A Light-weight Semaphore With Partial Spinning

Not solely that, however these implementations share some fascinating properties. They’re light-weight, within the sense that some operations occur solely in userspace, they usually can (optionally) spin for a brief interval earlier than sleeping within the kernel. You’ll discover the entire C++11 supply code on GitHub. Since the usual C++11 library doesn’t embody semaphores, I’ve additionally offered a conveyable Semaphore class that maps on to native semaphores on Home windows, MacOS, iOS, Linux and different POSIX environments. It’s best to have the ability to drop any of those primitives into virtually any present C++11 challenge.

A Semaphore Is Like a Bouncer

Think about a set of ready threads, lined up in a queue – very like a lineup in entrance of a busy nightclub or theatre. A semaphore is sort of a bouncer on the entrance of the lineup. He solely permits threads to proceed when instructed to take action.

Every thread decides for itself when to hitch the queue. Dijkstra referred to as this the P operation. P initially stood for some funny-sounding Dutch phrase, however in a contemporary semaphore implementation, you’re extra prone to see this operation referred to as wait. Mainly, when a thread calls the semaphore’s wait operation, it enters the lineup.

The bouncer, himself, solely wants to know a single instruction. Initially, Dijkstra referred to as this the V operation. These days, the operation goes by varied names, equivalent to submit, launch or sign. I want sign. Any operating thread can name sign at any time, and when it does, the bouncer releases precisely one ready thread from the queue. (Not essentially in the identical order they arrived.)

Now, what occurs if some thread calls sign earlier than there are any threads ready in line? No downside: As quickly as the subsequent thread arrives within the lineup, the bouncer will let it go immediately by means of. And if sign is named, say, 3 occasions on an empty lineup, the bouncer will let the subsequent 3 threads to reach go immediately by means of.

In fact, the bouncer must preserve monitor of this quantity, which is why all semaphores preserve an integer counter. sign increments the counter, and wait decrements it.

The great thing about this technique is that if wait is named some variety of occasions, and sign is named some variety of occasions, the result is at all times the identical: The bouncer will at all times launch the identical variety of threads, and there’ll at all times be the identical variety of threads left ready in line, whatever the order wherein these wait and sign calls occurred.

1. A Light-weight Mutex

I’ve already proven implement a light-weight mutex in an earlier post. I didn’t understand it on the time, however that submit was only one instance of a reusable sample. The trick is to construct one other mechanism in entrance of the semaphore, which I wish to name the field workplace.

The field workplace is the place the actual selections are made. Ought to the present thread wait in line? Ought to it bypass the queue solely? Ought to one other thread be launched from the queue? The field workplace can’t immediately examine what number of threads are ready on the semaphore, nor can it examine the semaphore’s present sign rely. As a substitute, the field workplace should by some means preserve monitor of its personal earlier selections. Within the case of a light-weight mutex, all it wants is an atomic counter. I’ll name this counter m_contention, because it retains monitor of what number of threads are concurrently contending for the mutex.

class LightweightMutex
    std::atomic<int> m_contention;         
    Semaphore m_semaphore;                 

When a thread decides to lock the mutex, it first visits the field workplace to increment m_contention.

    void lock()
        if (m_contention.fetch_add(1, std::memory_order_acquire) > 0)  

If the earlier worth was 0, meaning no different thread has contended for the mutex but. As such, the present thread instantly considers itself the brand new proprietor, bypasses the semaphore, returns from lock and proceeds into no matter code the mutex is meant to guard.

In any other case, if the earlier worth was better than 0, meaning one other thread is already thought of to personal the mutex. In that case, the present thread should wait in line for its flip.

When the earlier thread unlocks the mutex, it visits the field workplace to decrement the counter:

    void unlock()
        if (m_contention.fetch_sub(1, std::memory_order_release) > 1)  

If the earlier counter worth was 1, meaning no different threads arrived within the meantime, so there’s nothing else to do. m_contention is solely left at 0.

In any other case, if the earlier counter worth was better than 1, one other thread has tried to lock the mutex, and is subsequently ready within the queue. As such, we alert the bouncer that it’s now secure to launch the subsequent thread. That thread will probably be thought of the brand new proprietor.

Each go to to the field workplace is an indivisible, atomic operation. Due to this fact, even when a number of threads name lock and unlock concurrently, they may at all times go to the field workplace one by one. Moreover, the conduct of the mutex is fully decided by the choices made on the field workplace. After they go to the field workplace, they could function on the semaphore in an unpredictable order, however that’s OK. As I’ve already defined, the result will stay legitimate whatever the order wherein these semaphore operations happen. (Within the worst case, some threads might commerce locations in line.)

This class is taken into account “light-weight” as a result of it bypasses the semaphore when there’s no competition, thereby avoiding system calls. I’ve revealed it to GitHub as NonRecursiveBenaphore together with a recursive version. Nevertheless, there’s no want to make use of these lessons in observe. Most accessible mutex implementations are already lightweight. Nonetheless, they’re noteworthy for serving as inspiration for the remainder of the primitives described right here.

2. A Light-weight Auto-Reset Occasion Object

You don’t hear autoreset occasion objects mentioned fairly often, however as I discussed in my CppCon 2014 talk, they’re broadly utilized in recreation engines. Most frequently, they’re used to inform a single different thread (presumably sleeping) of obtainable work.

An autoreset occasion object is principally a semaphore that ignores redundant alerts. In different phrases, when sign is named a number of occasions, the occasion object’s sign rely won’t ever exceed 1. Which means you’ll be able to go forward and publish work items someplace, blindly calling sign after each. It’s a versatile approach that works even whenever you publish work items to some information construction aside from a queue.

Home windows has native help for occasion objects, however its SetEvent operate – the equal of sign – will be costly. One one machine, I timed it at 700 ns per name, even when the occasion was already signaled. In the event you’re publishing 1000’s of labor items between threads, the overhead for every SetEvent can shortly add up.

Fortunately, the field workplace/bouncer sample reduces this overhead considerably. All the autoreset occasion logic will be applied on the field workplace utilizing atomic operations, and the field workplace will invoke the semaphore solely when it’s completely essential for threads to attend.

I’ve revealed the implementation as AutoResetEvent. This time, the field workplace has a distinct option to preserve monitor of what number of threads have been despatched to attend within the queue. When m_status is unfavorable, its magnitude signifies what number of threads are ready:

class AutoResetEvent
    std::atomic<int> m_status;
    Semaphore m_sema;

Within the occasion object’s sign operation, we increment m_status atomically, as much as the restrict of 1:

    void sign()
        int oldStatus = m_status.load(std::memory_order_relaxed);
        for (;;)    
            assert(oldStatus <= 1);
            int newStatus = oldStatus < 1 ? oldStatus + 1 : 1;
            if (m_status.compare_exchange_weak(oldStatus, newStatus, std::memory_order_release, std::memory_order_relaxed))
        if (oldStatus < 0)

Be aware that as a result of the preliminary load from m_status is relaxed, it’s essential for the above code to name compare_exchange_weak even when m_status already equals 1. Because of commenter Tobias Brüll for pointing that out. See this README file for extra data.

3. A Light-weight Learn-Write Lock

Utilizing the identical field workplace/bouncer sample, it’s potential to implement a fairly good read-write lock. This read-write lock is totally lock-free within the absence of writers, it’s starvation-free for each readers and writers, and similar to the opposite primitives, it might spin earlier than placing threads to sleep. It requires two semaphores: one for ready readers, and one other for ready writers. The code is accessible as NonRecursiveRWLock.

4. One other Resolution to the Eating Philosophers Downside

The field workplace/bouncer sample may clear up Dijkstra’s dining philosophers problem in a manner that I haven’t seen described elsewhere. In the event you’re not accustomed to this downside, it entails philosophers that share dinner forks with one another. Every thinker should get hold of two particular forks earlier than she or he can eat. I don’t imagine this answer will show helpful to anyone, so I received’t go into nice element. I’m simply together with it as additional demonstration of semaphores’ versatility.

On this answer, we assign every thinker (thread) its personal devoted semaphore. The field workplace retains monitor of which philosophers are consuming, which of them have requested to eat, and the order wherein these requests arrived. With that data, the field workplace is ready to shepherd all philosophers by means of their bouncers in an optimum manner.

I’ve posted two implementations. One is DiningPhilosophers, which implements the field workplace utilizing a mutex. The opposite is LockReducedDiningPhilosophers, wherein each go to to the field workplace is lock-free.

5. A Light-weight Semaphore with Partial Spinning

You learn that proper: It’s potential to mix a semaphore with a field workplace to implement… one other semaphore.

See Also

Why would you do such a factor? As a result of you find yourself with a LightweightSemaphore. It turns into extraordinarily low cost when the lineup is empty and the sign rely climbs above zero, no matter how the underlying semaphore is applied. In such instances, the field workplace will rely solely on atomic operations, leaving the underlying semaphore untouched.

Not solely that, however you may make threads wait in a spin loop for a brief time period earlier than invoking the underlying semaphore. This trick helps keep away from costly system calls when the wait time finally ends up being brief.

Within the GitHub repository, the entire different primitives are applied on prime of LightweightSemaphore, relatively than utilizing Semaphore immediately. That’s how all of them inherit the flexibility to partially spin. LightweightSemaphore sits on prime of Semaphore, which in flip encapsulates a platform-specific semaphore.

The repository comes with a easy check suite, with every check case exercising a distinct primitive. It’s potential to take away LightweightSemaphore and drive all primitives to make use of Semaphore immediately. Listed below are the ensuing timings on my Home windows PC:

LightweightSemaphore Semaphore
testBenaphore 375 ms 5503 ms
testRecursiveBenaphore 393 ms 404 ms
testAutoResetEvent 593 ms 4665 ms
testRWLock 598 ms 7126 ms
testDiningPhilosophers 309 ms 580 ms

As you’ll be able to see, the check suite advantages considerably from LightweightSemaphore on this setting. Having stated that, I’m fairly positive the present spinning technique is just not optimum for each setting. It merely spins a hard and fast variety of 10000 occasions earlier than falling again on Semaphore. I appeared briefly into adaptive spinning, however one of the best method wasn’t apparent. Any solutions?

Comparability With Situation Variables

With all of those purposes, semaphores are extra general-purpose than I initially thought – and this wasn’t even a whole listing. So why are semaphores absent from the usual C++11 library? For a similar cause they’re absent from Enhance: a choice for mutexes and condition variables. From the library maintainers’ viewpoint, standard semaphore methods are simply too error prone.

When you concentrate on it, although, the field workplace/bouncer sample proven right here is actually simply an optimization for situation variables in a particular case – the case the place all situation variable operations are carried out on the finish of the vital part.

Contemplate the AutoResetEvent class described above. I’ve applied AutoResetEventCondVar, an equal class primarily based on a situation variable, in the identical repository. Its situation variable is at all times manipulated on the finish of the vital part.

void AutoResetEventCondVar::sign()
    std::unique_lock<std::mutex> lock(m_mutex);
    int oldStatus = m_status;
    if (oldStatus == 1)
    if (oldStatus < 0)

We are able to optimize AutoResetEventCondVar in two steps:

  1. Pull every situation variable exterior of its vital part and convert it to a semaphore. The order-independence of semaphore operations makes this secure. After this step, we’ve already applied the field workplace/bouncer sample. (Basically, this step additionally lets us keep away from a thundering herd when a number of threads are signaled directly.)

  2. Make the field workplace lock-free by converting all operations to CAS loops, enormously enhancing its scalability. This step leads to AutoResetEvent.

On my Home windows PC, utilizing AutoResetEvent rather than AutoResetEventCondVar makes the related check case run 10x quicker.

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