C++ Debt Paid in Full? Wait-Free, Lock-Free Queue

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In 2009 I wrote about a horrid lock-free Single Producer, Single Consumer Circular Fifo that I had seen in use in the industry. I tried to pick it apart and see what made it tick. Was it broken beyond reason or could it actually work? It was an attempt to understand without recommending the sketchy platform hack.

Of the C++ topics I have written that first article seemed to attract the biggest crowd at CodeProject.  A double-edged sword to say the least since I liked the feedback but did not like the thought of happy coders using something that was not at all kosher. Something that could break their shiny code when they least expected it.

Now with C++11 <atomic> it is a snap to write the wait-free, lock-free simple Single Producer, Single Consumer CircularFifo. Of all the lock-free structures out there, this got to be the easiest to grasp.

I just finished overwriting my old article. The old article is still saved with a nice revision tag but you have to dig to get to it.

For early reviewers here is my own snapshot of the revitalized article.  Its’ not yet spell corrected mirror but with nicer formatting can be found here CodeProject: Lock-Free Single Producer […]


Lock-Free Single-Producer – Single Consumer Circular Queue

Download lock-free-wait-free-circularfifo.zip
Latest lock-free-wait-free-circularfifo from BitBucket


The wait-free and lock-free circular queue is a useful technique for time and memory sensitive systems. The wait-free nature of the queue gives a fixed number of steps for each operation. The lock-free nature of the queue enables two thread communication from a single source thread (the Producer) to a single destination thread (the Consumer) without using any locks.

The power of wait-free and lock-free together makes this type of circular queue attractive in a range of areas, from interrupt and signal handlers to real-time systems or other time sensitive software.

Background: Circular FIFO Queue

This circular FIFO queue can be used for communicating between maximum two threads. This scenario is often referred to as the single producer → single consumer problem.

The problem description: A high priority task that must not be delayed in lenghty operations and also requires the data processing to finish in the same order as they are started. Examples could be : Interrupt/Signal handler, GUI events, data recorder, etc.

The solution: Delegate time consuming jobs to another thread that receives (i.e. consumes) the produced message. Using a FIFO queue gives predictable behaviour for the asynchronous delegation and processing of tasks as they pass from the Producer to the Consumer.

The Producer can add new tasks to the queue as long as the queue is not full. The Consumer can remove tasks from the queue as long as the queue is not empty. At the queue there is no waiting involved for adding or retrieving data. If there are no jobs to process the Consumer thread can continue with other tasks. If there is no room left in the queue for the Producer it is not required to wait until there is space.

Obviously a full queue for a Producer is a non-ideal situation. Its maximum size and how that relates to the negative impact of dealing with a full queue must be carefully considered. Issues that deals with this, such as overwrite of old items, multiple priority queues, or other ways of handling this scenario are outside the scope of this article.

Background: Article Rationale

Back in 2009 I published my first CodeProject article about a lock-free circular fifo queue. In the military avionic industry I had seen what was in my view a hazardous technique for creating a lock-free circular fifo. The queue was used for an interrupt handler as it pushed incoming messages from the interrupt handling to the real-time system.

If reading the original version of this article (also published here!) there will be a description and reasoning of the how, why and when a hazardous technique could possibly work and when it would not work. The old article was written to try to understand this clearly discouraged technique but without recommending it.

The old article described a type of thread communication that goes against good C++ practice using a circular fifo queue that is highly platform dependent. It breaks easily as it is basically an ugly platform hack that looks appealing through an illusion of simplicity. It could break for something as simple as a compiler update or using it on another hardware architecture.

In the old article I gave a promise to publish a C++11 empowered queue that is lock-free through the use of std::atomic. That time has come now. C++11 with its memory model, is available both on Linux and Windows. Using the std::atomic from the ‹atomic› library effectively removes the need to ever again being tempted to use discouraged platform dependent hacks.

The aim with the article is not only to show two wait-free, lock-free CircularFifo queues. The article is also explaining the rules governing the C++11 memory models. After reading this article you should have an understanding of some of the fundamentals behind the ‹atomic› library.


For those of you who want to read up on the inner workings of the Circular Queue, I have provided a short description of it and my implementation in Part I. For those of you who are already familiar with it can shorten this read by going to Part II. Part II describes briefly the C++11 different memory models and how they with std::atomic are used to create the lock-free aspect of these circular queues.


Lock-free, really? But …
The C++11 standard guarantees that the std::atomic_flag is lock-free. In fact the std::atomic_flag is the only type that is guaranteed to be lock-free. It is possible that some platform/library implementations will use locks internally for the native atomic types. However, although this is system dependent it is likely that many native atomic types are lock-free.

The CircularFifo provides a function bool isLockFree() const {...} that can be called to see if it is truly lock-free, even behind the scenes. ´

But what about …
Just like in the old CodeProject article this text is written to be simple and easy to understand. All the nitty-gritty details that an optimal solution might have are not covered. These details are usually in the area of:

  • Consumer/Producer handling for empty/full queues.
  • Handling of variable sized items

Multiple Producers, Multiple Consumers
Never use multiples of either Consumer or Producer for this queue.
Using more Producer or Consumer threads breaks this design and corrupts the queue. This queue must only be used in a single Producer and single Consumer scenario. If more threads are needed, then a different solution should be used.

Nothing New!
This article does not claim to introduce a new concept, or a new way of writing this type of lock-free circular queue. On the contrary, this article presents as far as I understand a well known, widely accepted way of writing such a queue. The resulting code is in fact remarkably similar to the old code, almost identical. Comparing the code might give an illusion of only trivial code changes but the impact of the changes is enourmous. The real difference is the atomic declaration and handling. This is of course a huge difference since there are lots of things happening behind the scenes

The old code should be considered broken and where the old code is not guaranteed to work by any standard the code presented here should work according to the new C++11 standard [2].

Public Domain
Use the code on your own risk. I am using it myself of course but because of the Public Domain status I will not give any guarantees. Nor will I give any promises in case of bugs that might have slipped me by. Using the code or not is your own responsibility. Using the code can be done freely with no obligations to me or towards a license. Modify and use the code to your hearts content.

Tail first or Head first?
Should items be added at the tail and removed at the head, or is the opposite more logical? The opinions differ. This article uses the methodology of “items are added at the tail, removed from the head” to be consistent with the old article and to make it similar with the common and well-known pop_front and push_back queue operations.

Memory model: sequential or relaxed/acquire/release?

Two versions of the wait and lock-free circular fifo are presented. The first, most intuitive, use C++11 default memory-ordering memory_order_seq_cst. The other, somewhat more complicated, use memory_order_relaxed, memory_order_acquire and memory_order_release. The use of the memory orders will be explained and I will also try to show that the default memory_order_seq_cst is not only the easiest to reason about but also has very good performance on x86-x64 architectures.

Part I

Using the code

Please remember to use only one thread as the Producer and only one thread as the Consumer. If more threads are involved on either side it will break the thread-safe design and corrupt the Producer → Consumer communication.

It could not be any simpler to use the code.

CircularFifo‹Message, 128› queue;     // 128 'Messages' will fit

/* Producer thread */
Message m = ...
if ( false == queue.push(m)) { /*false equals full queue */ }

/* Consumer thread */
Message m;
if ( false == queue.pop(m)) { /* false equals empty queue */ }

You can find more examples in the unit tests that come with the code.

Code Explained: Circularfifo‹Type, Size›

Let us go straight to the sequential consistent code without further ado. The code is slightly simplified to increase article readability. If you prefer the full syntax you could open up the code and view it side-by-side.

template‹typename Element, size_t Size›
class CircularFifo{
  enum { Capacity = Size+1 };

  CircularFifo() : _tail(0), _head(0){}
  virtual ~CircularFifo() {}

  bool push(const Element& item);
  bool pop(Element& item);

  bool wasEmpty() const;
  bool wasFull() const;
  bool isLockFree() const;

  size_t increment(size_t idx) const;

  std::atomic‹size_t›  _tail;
  Element              _array[Capacity];
  std::atomic‹size_t›  _head;

How it works

The first described queue uses the default, sequential atomic operations. The sequential model makes it easy to reason about the atomics and how they relate in respect to atomic operations in other threads. On the strong hardware memory (e.g. processor) architectures that x86 and x64 have it gives some performance overhead when using the sequential atomic CircularFifo compared to the later discussed CircularFifo that uses fine grained std::memory_order_{relaxed/acquire/release}.

On a weakly ordered memory architecture the performance difference between the queues would be more significant.

Push and Pop
bool push(Item&) will be done by a Producer thread. The bool pop(Item&) will be used by the Consumer thread.


When the buffer is empty, both indexes will be the same. Any reads by the Consumer will fail.

bool wasEmpty() const
  return (_head.load() == _tail.load());

Any attempts by the Consumer to retrieve, bool pop(Item&), when the queue is empty will fail. Checking if the queue is empty with wasEmpty() will give a snapshot of the queue status. Of course the empty status might change before the reader has even acted on it. This is OK and fine, it should be treated as a snapshot and nothing else.

Producer adds items

The Producer adds, push(), a new item at the position indexed by the tail. After writing, the tail is incremented one step, or wrapped to the beginning if at end of the queue. The queue grows with the tail.

/* Producer only: updates tail index <strong>after</strong> setting the element in place */
bool push(Element& item_)
  auto current_tail = _tail.load();
  auto next_tail = increment(current_tail);
  if(next_tail != _head.load())
    _array[current_tail] = item;
    return true;

  return false;  // full queue

The Producer adds another item and the tail is incremented again.

Consumer retrieves item

The Consumer retrieves, pop(), the item indexed by the head. The head is moved toward the tail as it is incremented one step. The queue shrinks with the head.

/* Consumer only: updates head index <strong>after</strong> retrieving the element */
bool pop(Element& item)
  const auto current_head = _head.load();
  if(current_head == _tail.load())
    return false;   // empty queue

  item = _array[current_head];
  return true;


If the Producer pushes more items onto the queue than the Consumer can keep up with, the queue will eventually become full.

When the queue is full, there will be a one slot difference between head and tail. At this point, any writes by the Producer will fail. Yes it must even fail since otherwise the empty queue criterion i.e. head == tail would come true.

bool wasFull() const
  const auto next_tail = increment(_tail.load());
  return (next_tail == _head.load());

size_t increment(size_t idx) const
  return (idx + 1) % Capacity;

% modulus operator
The % modulus operator can be confusing if not encountered before. The % operator gives the remainder from integer division. It can be used in a range of ways and here it is used to calculate when the index should be wrapped back to the beginning in a circular way.

 // Example: A CircularFifo with Size of 99
 // Capacity is Size+1. The padding of +1 is used to simplify the logic
 increment(98) ---> will yield 99
 increment(99) ---> will yield 0

When the next_tail showed in push() is one larger then the queue’s size it wraps back to the beginning, i.e index 0.

Thread Safe Use and Implementation

The thread safety is ensured through the class design and its intented use. Only two functions can modify the state of the queue, push() and pop(). Only one thread should be allowed to touch push(). Only one thread should be allowed to touch pop(). Thread safety is guaranteed in this way when push() and pop() are used by a at most one corresponding thread. The Producer thread should only access push() and the Consumer thread only pop().

The design can be further emphasized with access through interfaces
but for this article I think it is enough to clarify it here and in the comments. For a real-world project it might make sense to use something like SingleConsumerInputQueue and SingleProducerOutputQueue interfaces to decrease the risk for error by confusion.

Atomic access when used the intended way
Producer: push() writes only to the tail, but reads a head snapshot to verify queue is not full.

Consumer: pop() writes only to the head, but reads a tail snapshot to verify that the queue is not empty. Only the Producer thread will update tail and only the Consumer thread will update head.

However reading and writing of both tail and head must be thread safe in the sense that we do not want to read old, cached values and both reads and writes must be atomic. As explained below the update of tail and head indexes are atomic. The atomic read/write together with this class design will ensure thread safety for at most one Producer thread and one Consumer thread.

Important: The text further down explains how atomic, non-reordered reads and writes are achieved for this Circular Queue. It is probably the most important part of this article. It explaines both the sequential and the acquire-release/relaxed models.

Part II

Making It Work

It is imperative that the head and tail indexes must be updated only after the element (pop() or push()) is read or written. Thus, any updates to the head or tail will ensure proper access to the elements. For this to work, the read and writes of the head and tail must be atomic and must not be re-ordered.

Atomic operations and the different Memory Models

Below is described a subset of the functionality that you can get from the different C++11 memory models and atomic operations. It is in no way comprehensive but contains the necessary pieces to explain both types of the C++11 empowered wait-free, lock-free circular fifo.

There are three different memory-ordering models in C++11 and with them six ordering options.

  1. Sequentially consistent model
    • memory_order_seq_cst
  2. acquire-release model
    • memory_order_consume
    • memory_order_acquire
    • memory_order_release
    • memory_order_acq_rel
  3. relaxed model
    • memory_order_relaxed

Sequential Consistent

The default, sequential memory ordering is used in the code example above. This atomic, sequentially consistent memory model is probably what most of us are comfortable with when reasoning about possibly sequences of threaded atomic operations.

Rules for Sequential Consistent Memory Model and Operations

  1. A sequential consistent store will be synchronized with a sequential consistent load of the same data. It is guaranteed thanks to a global synchronization between involved threads.
  2. All threads participating in these sequential atomic operations will see exactly the same order of the operations.
  3. Atomic operations within the same thread cannot be reordered.
  4. A seqence of atomic operations in one thread will have the same sequence of
    order seen by other threads

Sequential Consistent Atmic Code

These rules give that the sequential atomic operations used in push() and pop() are safe. Let us recap with pop() to demonstrate this:

/* Consumer only: updates head index <strong>after</strong> retrieving the element */
bool pop(Element& item)
  const auto current_head = _head.load();  // 1. loads sequentially the head
  if(current_head == _tail.load())         // 2. compares head to snapshot of tail
    return false;   // empty queue

  item = _array[current_head];             // 3. retrievs the item pointed to by head
  _head.store(increment(current_head));    // 4. update the head index to new position
  return true;

If the step 3. or 4. would be rearranged the queue would be corrupted. The atomic sequential rules guarantee that no such reordering will happen. The same set of rules give that the Consumer thread will not get out-of-order updates when reading the tail snapshot with head.load()

It is with this sequential memory model you can get this warm fuzzy feeling in your stomach. It seems easy to reason about, right?

Caveats with the Sequential Memory Model

Caveat 1:
Non-sequential, relaxed memory atomic operations might not see the same ordering of operations as the sequential, atomic, operations. To get the power of easy-to-reason-about ordering of operations the sequentially consistent memory ordering should be used for all atomic operations that are interacting.

Caveat 2:
On the x86-x64 processor architecture which use a strong hardware memory model [6] the sequential consistent model is relatively cheap. On a weakly-ordered hardware memory architecture [7] the sequential consistent model is more expensive as it requires more internal synchronization operations. On such weakly-ordered hardware memory architecture the sequential consistent model will have a significant performance penalty due to much higher synchronization overhead then the acquire-release memory model.

Simplified Atomic Sequential operations

One last thing on the sequential atomic operations:
Not only are they easy to reason about they are also easier to write. Since they are the default choice it is not necessary to write explicitly the memory operation type.

bool CircularFifo::wasFull() const
  auto index = _tail.load();
  auto next_tail = (index + 1) % Capacity;
  return (next_tail == _head.load());

Using the default means that you can write _tail.load() and not specify the memory order. You can of course explicitly write that it is using the sequential consistent memory order std::memory_order_seq_cst

bool CircularFifo::wasFull() const
auto index = _tail.load(std::memory_order_seq_cst);
auto next_tail = (index + 1) % Capacity;
return (next_tail == _head.load(std::memory_order_seq_cst));

Refined Memory Order

Using the fine grained memory models acquire-release and relaxed, together can squeeze out better performance thanks to less synchronization overhead. The nice to reason about global synchronization guarantee from the sequential consistent model is no longer there.

Threads may now see different views of the interacting atomic operations. It is time to thread (pun intended) very carefully. Quoting Anthony Williams: [1, chapter 5.3.3 Memory ordering for atomic operations]

“In the absence of other ordering constraints, the only requirements is that all threads agree on the modification order of each individual variable”

Below are written short, simplified examples for the two fine-grained memory models, relaxed and acquire-release.  The area is more advanced then explained here but should be enough to make the lock-free code comprehensible can work as an initial  introduction to the fine grained atomic operations.

Relaxed-Memory Model

The relaxed atomic operations can be powerful if used together with acquire-release operations. By itself the relaxed operations can cause quite a bit of confusion for the unwary.

Rules for the Relaxed Memory Model and Operations

  1. Relaxed atomic opertions on the same variable, on the same thread guarantee happens-before ordering within that same thread.
  2. Operations on the same thread, on the same variable will not be reordered
  3. For a synchronized ordering between threads there must be a pair of acquire – release.
  4. Only the modification order of the atomic operations on a variable is communicated to other threads, but as the relaxed memory operation does not use synchronize-with the result may surprise you…

Releaxed-Memory operations example

Example inspired from C++11 standard [2, §29.3 Atomics Opertions Library: “Order and Consistency”]

 // A possible thread interleaving snapshot, i.e. below is an
 // possible 'chronological' order of events between two threads
 // as they actually "happen"

 // x, y are initially zero

 // thread_1
 auto r1 = y.load(std::memory_order_relaxed);    // t1: 1
 x.store(r1, std::memory_order_relaxed);         // t1: 2

 // thread_2
 auto r2 = x.load(std:memory_order_relaxed);     // t2: 1
 y.store(123, std::memory_order_relaxed);        // t2: 2

These are thread operations that are memory unordered. Even if the thread interleaving snapshot happens in the above chronological order the events can impact in a different sequence.

I.e. the following impact sequence is possible

 y.store(123, std::memory_order_relaxed);        // t2: 2
 auto r1 = y.load(std::memory_order_relaxed);    // t1: 1
 x.store(r1, std::memory_order_relaxed);         // t1: 2
 auto r2 = x.load(std:memory_order_relaxed);     // t2: 1

Resulting in r1 = r2 = 123;

Acquire-Release Memory model

The acquire-release memory model give some guarantees for thread synchronization

Rules for the Acquire-Release Memory Model and Operations

  1. No guaranteed order for all atomic operations
  2. Still, it has stronger synchronization orderings than relaxed
  3. Guaranteed thread-pair ordering synchronization. I.e.between the thread that does release and the thread that does acquire
  4. Reordering is restricted but still not sequential…
     // thread_1:
     y.store(true, std::memory_order_release);

    It is guaranteed that thread_2 will, at some point, see that y is true and exit the while-loop. The memory_order_release synchronizes with the memory_order_acquire.

  5. Relaxed operations obey a happens-before rule that can be used together with acquire-release operations…
     // thread_1
     x.store(123, std::memory_order_releaxed); // relaxed X happens-before Y store
     y.store(true, std::memory_order_release);
     // thread_2
     assert(123 == x.load(std::memory_order_relaxed));

    The happens-before relationship guarantees that there will be no assert failure in assert(123 == x.load(relaxed)). Since the thread_1: x.store(123,relaxed) happens-before the y.store(true, release) it is guaranteed that when thread_2: reads true == y.load(acquire) the value of x must already be 123.

Code Explained: Acquire-Release/Relaxed Circularfifo

The fine grained memory models and operations explained above can be used to create even more effective push() and pop() operations.

Remember that the Producer could only update one variable (tail) and the Consumer could only update one member variable (head).

The relexed memory operation is only used for loading the atomic variable in that very thread that is responsible for updating the variable. Within the same thread the relaxed operation cannot be reordered for the variable.

bool push(const Element& item)

bool push(const Element& item)
  const auto current_tail = _tail.load(std::memory_order_relaxed);  // 1
  const auto next_tail = increment(current_tail);
  if(next_tail != _head.load(std::memory_order_acquire))            // 2
    _array[current_tail] = item;                                    // 3
    _tail.store(next_tail, std::memory_order_release);              // 4
    return true;
  return false; // full queue
  1. Relaxed loading of the tail value. Since the Producer thread is the only thread calling push() it is guaranteed that the tail value will be the latest. No cross-thread synchronization is needed for the load.
  2. The next_tail is compared against the head value snapshot. The head value is pair-wise acquire-release synchronized. It is guaranteed to never come out-of-order with following headupdates.
  3. The item is saved in the position pointed to by the not-yet-synchronized next_tail. This happens-before the release store in (4) and is guaranteed that the save is seen before (4).
  4. The tail is updated with release order. Pair-synchronization with the Consumer thread is guaranteed with the Consumer’s acquire reading of tail.

bool pop(const Element& item)

bool pop(Element& item)
  const auto current_head = _head.load(std::memory_order_relaxed);    // 1
  if(current_head == _tail.load(std::memory_order_acquire))           // 2
    return false; // empty queue

  item = _array[current_head];                                       // 3
  _head.store(increment(current_head), std::memory_order_release);   // 4
  return true;
  1. Relaxed loading of the head value. Since the Consumer thread is the only thread calling pop() it is guaranteed that the head value will be the latest. No cross-thread synchronization is needed for the load.
  2. The current_head is compared against the tail value snapshot. The tail value is pair-wise acquire-release synchronized. It is guaranteed to never come out-of-order with following tailupdates.
  3. The item is retrieved from the position pointed to by the current_head. This happens-before the release store in (4).
  4. The head is updated with release order. Pair-wise synchronization with the Producer’s thread is guaranteed with the Producer’s acquire reading of tail.

There is thread-pair ordering synchronization between the Producer and the Consumer for tail and head. The Producer can never see out-of-order updates for the Consumer updated head and vice-versa for tail.

x86-x64 Comparison: Sequential vs Refined Memory Order

So does it really matter if using the acquire-release-relaxed type of CircularFifo compared to the sequential?

A very quick and not very scientific test both on Windows (VS2012) and Linux (gcc 4.7.2) showed that

  • Windows (x64): acquire-release was approximately 23% faster then the sequential.
  • Windows (x86): acquire-release was approximately 22% faster then the sequential.
  • Linux (x64): acquire-release was approximately 44% faster then the sequential.
  • Linux (x68): acquire-release was approximately 36% faster then the sequential.


When I wrote the original article it was a platform hack. Such hacks were never necessary but are now explicitly obsolete. With C++11 std::atomic can supply all the needed functinality. The big caveat is that apart from the sequential consistent model it is pretty hard to reason about how the operations interact.

The sequential consistent model is easier to reason about and to implement in a simple structure such as the CircularFifo. Whether or not you use that one or the acquire-release type is up to you.

Finally I have reached the end of this long article. Thank you for reading it. Any comments, improvment suggestions or questions are more then welcome.


  • 3rd November, 2009: Initial version
  • […]
  • 27th November, 2012: Complete rewrite. Using C++11 atomics, showing sequential consistent and acquire-release, relaxed ordered atomics to build the CircularFifo.


  1. Anthony Williams book C++ Concurrency in Action: Practical Multithreading
  2. C++11 ISO IEC_14882:2011 (costs $)”.
    A free, slightly newer draft (n3337) version (but contains more than the standard).
    An older, free draft, version (n3242)
  3. The original version of this article. Warning: highly platform dependent
  4. Wikipedia on FIFO queues
  5. std::atomic_flag class
  6. Explained: Weak vs Strong Memory Models(Preshing on programming)
  7. Example of weakly-ordered hardware memory model (Preshing on programming)

About kjellkod

Software Engineer by trade, (former?) Martial Artist and Champion by strong will and small skill... and a Swede by nationality :)
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17 Responses to C++ Debt Paid in Full? Wait-Free, Lock-Free Queue

  1. Mmm… I think the first snippet showing “push” is broken:
    shouldn’t the condition to update current_tail position be
    if (next_tail != _head.load()) ?

  2. Marek says:

    Nice article, I have a question: Will there be big difference in performance if the Element type and Size are small enough that _head and _tail end in the same cache line (false sharing)?

    I also saw in one video that operator modulo can be slow on Intel’s processors (it can be executed only in one “port”) so rounding to nearest power of 2 and bit-masking size is faster than % (can be executed in any processor’s “port”).

    • kjellkod says:

      Thank you Marek,

      False sharing can be a problem if it happens to often,.. I have not tried to create that problem artificially. Either way unless it is very-unlucky this is a cache-friendly structure and should for that reason perform quite well compared to other common lock-free structures (such as a list).

      This CircularFifo is quite simple. Two approaches that I have either seen or heard about is
      1) exactly what you suggest: power of two and bit masking
      2) using if-case to act on wrap-around
      3) let the natural type wrap-around instead. I.e. just continue to increment tail/head. The empty/full and position in the queue can be calculated.

      Whether or not 1-3 is more effective then % operator I leave up to whomever feel inspired to test it. I do believe that the atomic synchronization will completely and utterly overshadow any possible gains from using 1-3 over %-operator. But I could be wrong of course. Only testing can tell.

  3. tala says:

    Great article!
    I tend to look at caveats in a difference way and believe in knowing the right tool to use for each case if possible, especially when the hood is now open and you are so close to hardware (:

    BTW what about fences (memory barriers) ? they can be used to order relax operation as well.

  4. kjellkod says:

    Thank you T.A for the praise
    I postponed this ‘blog-article’ since g2log changes were in demand… I am glad to hear that at least one g2log-user liked it =)

    Yes fences would work too. Have you seen Jeff Preshing’s blog http://preshing.com? He does a great job at explaining this and other low-level lock-free and memory model intricacies

  5. Piers says:

    Thanks for the post Kjell.

    Could I use this lock free queue with Qt QAtomicInt?

    i.e. swapping

    std::atomic _tail;
    std::atomic _head;


    QAtomicInt _tail;
    QAtomicInt _head;

    I have done this but am crashing with :
    *** glibc detected *** ./Main malloc(): smallbin double linked list corrupted: 0x00…

  6. piers says:

    It’s okay, the memory corruption was coming from elsewhere. I choose your SPSC queue code as it was very easy to replace a QQueue/QMutex based queue in a Qt 4.8 project I’m working on with your code to make a quick locking vs lock free performance comparison.
    Thanks again.

  7. Summer says:

    Hmmmm. I’m getting multiple instances where pop() returns true even though the fifo is empty (or some similar behavior)! I’m using it to write to a file, and you can see identical messages consistently repeated 2 – 3 times each in the file. Is it possible I’m using it incorrectly? I’m just pushing in one thread, and popping in the other.

    It looks like one can just call push() and pop() without regard to empty() and full() as long as you handle p & p returning false, but maybe I’m mistaken. Regards!

  8. Under the heading ‘Code Explained: Acquire-Release/Relaxed Circularfifo’, in the ‘bool push(const Element& item)’ example, in the text for #3 you write “The item is saved in the position pointed to by the not-yet-synchronized next_tail.” but did you mean current_tail? I find it a bit confusing.

  9. By the way, great blog post, really complete and explanatory.

  10. plasmacel says:

    Excellent articel! How would you implement a size() function to return the number of elements in the queue?

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