I can't find a semantic difference between lock-based and lock-free atomics. So far as I can tell, the difference is semantically meaningless as far as the language is concerned, since the language doesn't provide any timing guarantees. The only guarantees I can find are memory ordering guarantees, which seem to be the same for both cases.
(How) can the lock-free-ness of atomics affect program semantics?
i.e., aside from calling is_lock_free or atomic_is_lock_free, is it possible to write a well-defined program whose behavior is actually affected by whether atomics are lock-free?
Do those functions even have a semantic meaning? Or are they just practical hacks for writing responsive programs even though the language never provides timing guarantees in the first place?
There is at least one semantic difference.
As per C++11 1.9 Program execution /6:
When the processing of the abstract machine is interrupted by receipt of a signal, the values of objects which are neither of type volatile std::sig_atomic_t nor lock-free atomic objects are unspecified during the execution of the signal handler, and the value of any object not in either of
these two categories that is modified by the handler becomes undefined.
In other words, it's safe to muck about with those two categories of variables but any access or modification to all other categories should be avoided.
Of course you could argue that it's no longer a well defined program if you invoke unspecified/undefined behaviour like that but I'm not entirely sure whether you meant that or well-formed (i.e., compilable).
But, even if you discount that semantic difference, a performance difference is worth having. If I had to have a value for communicating between threads, I'd probably choose, in order of preference:
the smallest adequate data type that was lock-free.
a larger data type than necessary, if it was lock-free and the smaller one wasn't.
a shared region fully capable of race conditions, but in conjunction with an atomic_flag (guaranteed to be lock-free) to control access.
This behaviour could be selected at compile or run time based on the ATOMIC_x_LOCK_FREE macros so that, even though the program behaves the same regardless, the optimal method for that behaviour is chosen.
In C++11 Standard, the term "lock-free" was not defined well as reported in issue LWG #2075.
C++14 Standard define what lock-free executions is in C++ language (N3927 approved).
Quote C++14 1.10[intro.multithread]/paragraph 4:
Executions of atomic functions that are either defined to be lock-free (29.7) or indicated as lock-free (29.4) are lock-free executions.
If there is only one unblocked thread, a lock-free execution in that thread shall complete. [ Note: Concurrently executing threads may prevent progress of a lock-free execution. For example, this situation can occur with load-locked store-conditional implementations. This property is sometimes termed obstruction-free. -- end note ]
When one or more lock-free executions run concurrently, at least one should complete. [ Note: It is difficult for some implementations to provide absolute guarantees to this effect, since repeated and particularly inopportune interference from other threads may prevent forward progress, e.g., by repeatedly stealing a cache line for unrelated purposes between load-locked and store-conditional instructions. Implementations should ensure that such effects cannot indefinitely delay progress under expected operating conditions, and that such anomalies can therefore safely be ignored by programmers. Outside this International Standard, this property is sometimes termed lock-free. -- end note ]
Above definition of "lock-free" depends on what does unblocked thread behave. C++ Standard does not define unblocked thread directly, but 17.3.3[defns.blocked] defines blocked thread:
a thread that is waiting for some condition (other than the availability of a processor) to be satisfied before it can continue execution
(How) can the lock-free-ness of atomics affect program semantics?
I think the answer is NO, except signal handler as paxdiablo's answer, when "program semantics" mean the side effects of atomic operations.
The lock-free-ness of atomic affect the strength of progress guarantee for whole multithreading program.
When two (or more) threads concurrently execute lock-free atomic operations on same object, at least one of these operations should complete under any worst thread scheduling.
In other words, 'evil' thread scheduler could intentionally block progress of lock-based atomic operations in theory.
Paxdiablo has answered pretty well, but some background might help.
"Lock-free atomic" is a bit of redundant terminology. The point of atomic variables, as they were originally invented, is to avoid locks by leveraging hardware guarantees. But, each platform has its own limitations, and C++ is highly portable. So the implementation has to emulate atomicity (usually via the library) using fine-grained locks for atomic types that don't really exist at the hardware level.
Behavioral differences are minimized between hardware atomics and "software atomics," because differences would mean lost portability. On the other hand, a program should be able to avoid accidentally using mutexes, hence introspection through ATOMIC_x_LOCK_FREE which is available to the preprocessor.
Related
If T is a C++ fundamental type, and if std::atomic<T>::is_lock_free() returns true, then is there anything in std::atomic<T> that is wait-free (not just lock-free)? Like, load, store, fetch_add, fetch_sub, compare_exchange_weak, and compare_exchange_strong.
Can you also answer based on what is specified in the C++ Standard, and what is implemented in Clang and/or GCC (your version of choice).
My favorite definitions for lock-free and wait-free are taken from C++ Concurrency in Action (available for free). An algorithm is lock-free if it satisfies the first condition bellow, and it is wait-free if it satisfies both conditions below:
If one of the threads accessing the data structure is suspended by the scheduler midway through its operation, the other threads must still be able to complete their operations without waiting for the suspended thread.
Every thread accessing the data structure can complete its operation within a bounded number of steps, regardless of the behavior of other threads.
There exist universally accepted definitions of lock-freedom and wait-freedom, and the definitions provided in your question are consistent with those. And I would strongly assume that the C++ standard committee certainly sticks to definitions that are universally accepted in the scientific community.
In general, publications on lock-free/wait-free algorithms assume that CPU instructions are wait-free. Instead, the arguments about progress guarantees focus on the software algorithm.
Based on this assumption I would argue that any std::atomic method that can be translated to a single atomic instruction for some architecture is wait-free on that specific architecture. Whether such a translation is possible sometimes depends on how the method is used though. Take for example fetch_or. On x86 this can be translated to lock or, but only if you do not use its return value, because this instruction does not provide the original value. If you use the return value, then the compiler will create a CAS-loop, which is lock-free, but not wait-free. (And the same goes for fetch_and/fetch_xor.)
So which methods are actually wait-free depends not only on the compiler, but mostly on the target architecture.
Whether it is technically correct to assume that a single instruction is actually wait-free or not is a rather philosophical one IMHO. True, it might not be guaranteed that an instruction finishes execution within a bounded number of "steps" (whatever such a step might be), but the machine instruction is still the smallest unit on the lowest level that we can see and control. Actually, if you cannot assume that a single instruction is wait-free, then strictly speaking it is not possible to run any real-time code on that architecture, because real-time also requires strict bounds on time/the number of steps.
This is what the C++17 standard states in [intro.progress]:
Executions of atomic functions that are either defined to be lock-free (32.8) or indicated as lock-free (32.5)
are lock-free executions.
If there is only one thread that is not blocked (3.6) in a standard library function, a lock-free execution in that thread shall complete. [ Note: Concurrently executing threads may prevent progress of a lock-free
execution. For example, this situation can occur with load-locked store-conditional implementations. This property is sometimes termed obstruction-free. — end note ]
When one or more lock-free executions run concurrently, at least one should complete. [ Note: It is difficult for some implementations to provide absolute guarantees to this effect, since repeated and particularly inopportune interference from other threads may prevent forward progress, e.g., by repeatedly stealing a cache line for unrelated purposes between load-locked and store-conditional instructions. Implementations should ensure that such effects cannot indefinitely delay progress under expected operating conditions, and that such anomalies can therefore safely be ignored by programmers. Outside this document, this property is sometimes termed lock-free. — end note ]
The other answer correctly pointed out that my original answer was a bit imprecise, since there exist two stronger subtypes of wait-freedom.
wait-free - A method is wait-free if it guarantees that every call finishes its execution in a finite number of steps, i.e., it is not possible to determine an upper bound, but it must still be guaranteed that the number of steps is finite.
wait-free bounded - A method is wait-free bounded if it guarantees that every call finishes its execution in a bounded number of steps, where this bound may depend on the number of threads.
wait-free population oblivious - A method is wait-free population oblivious if it guarantees that every call finishes its execution in a bounded number of steps, and this bound does not depend on the number of threads.
So strictly speaking, the definition in the question is consistent with the definition of wait-free bounded.
In practice, most wait-free algorithms are actually wait-free bounded or even wait-free population oblivious, i.e., it is possible to determine an upper bound on the number of steps.
Since there are many definitions of wait-freedom1 and people choose different ones, I think that a precise definition is paramount, and a distinction between its specializations is necessary and useful.
These are the universally accepted definitions of wait-freedom and its specializations:
wait-free:
All threads will make progress in a finite number of steps.
wait-free bounded:
All threads will make progress in a bounded number of steps, which may depend on the number of threads.
wait-free population-oblivious3:
All threads will make progress in a fixed number of steps, that does not depend on the number of threads.
Overall, the C++ standard makes no distinction between lock-free and wait-free (see this other answer). It always gives guarantees no stronger than lock-free.
When std::atomic<T>::is_lock_free() returns true, instead of mutexes the implementation utilizes atomic instructions possibly with CAS loops or LL/SC loops.
Atomic instructions are wait-free. CAS and LL/SC loops are lock-free.
How a method is implemented depends on many factors, including its usage, the compiler, the target architecture and its version. For example:
As someone says, on x86 gcc, fetch_add() for std::atomic<double> uses a CAS loop (lock cmpxchg), while for std::atomic<int> uses lock add or lock xadd.
As someone else says, on architectures featuring LL/SC instructions, fetch_add() uses a LL/SC loop if no better instructions are available. For example, this is not the case on ARM versions 8.1 and above, where ldaddal is used for non-relaxed std::atomic<int> and ldadd is used if relaxed.
As stated in this other answer, on x86 gcc fetch_or() uses lock or if the return value is not used, otherwise it uses a CAS loop (lock cmpxchg).
As explained in this answer of mine:
The store() method and lock add, lock xadd, lock or instructions are wait-free population-oblivious, while their "algorithm", that is the work performed by the hardware to lock the cache line, is wait-free bounded.
The load() method is always wait-free population-oblivious.
1 For example:
all threads will make progress in a finite number of steps (source)
all threads will make progress in a bounded number of steps2
per "step" that they all execute, all threads will make forward progress without any starvation (source)
2 It is not clear whether the bound is constant, or it may depend on the number of threads.
3 A strange name and not good for an acronym, so maybe another one should be chosen.
This could be a language neutral question, but in practice I'm interested with the C++ case: how are multithread programs written in C++ versions that support MT programming, that is modern C++ with a memory model, ever proven correct?
In old C++, MT programs were just written in term of pthread semantics and validated in term of the pthread rules which was conceptually easy: use primitives correctly and avoid data races.
Now, the C++ language semantic is defined in term of a memory model and not in term of sequential execution of primitive steps. (Also the standard mentions an "abstract machine" but I don't understand any more what it means.)
How are C++ programs proven correct with that non sequential semantic? How can anyone reason about a program that is not doing primitive steps one after the other?
It is "conceptually easier" with the C++ memory model than it was with pthreads prior to the C++ memory model. C++ prior to the memory model interacting with pthreads was loosely specified, and reasonable interpretations of the specification permitted the compiler to "introduce" data races, so it is extremely difficult (if possible at all) to reason about or prove correctness for MT algorithms in the context of older C++ with pthreads.
There seems to be a fundamental misunderstanding in the question in that C++ was never defined as a sequential execution of primitive steps. It has always been the case that there is a partial ordering between expression evaluations. And the compiler is allowed to move such expressions around unless constrained from doing so. This was unchanged by the introduction of the memory model. The memory model introduced a partial order for evaluations between separate threads of execution.
The advice "use the primitives correctly and avoid data races" still applies, but the C++ memory model more strictly and precisely constrains the interaction between the primitives and the rest of the language, allowing more precise reasoning.
In practice, it is not easy to prove correctness in either context. Most programs are not proven to be data race free. One tries to encapsulate as much as possible any synchronization so as to allow reasoning about smaller components, some of which can be proven correct. And one uses tools such as address sanitizer and thread sanitizer to catch data races.
On data races, POSIX says:
Applications shall ensure that access to any memory location by more than one thread of control (threads or processes) is restricted such that no thread of control can read or modify a memory location while another thread of control may be modifying it. Such access is restricted using functions that synchronize thread execution and also synchronize memory with respect to other threads.... Applications may allow more than one thread of control to read a memory location simultaneously.
On data races, C++ says:
The execution of a program contains a data race if it contains two potentially concurrent conflicting actions, at least one of which is not atomic, and neither happens before the other, except for the special case for signal handlers described below. Any such data race results in undefined behavior.
C++ defines more terms and tries to be more precise. The gist of this is that both forbid data races, which in both, are defined as conflicting accesses, without the use of the synchronization primitives.
POSIX says that the pthread functions synchronize memory with respect to other threads. That is underspecified. One could reasonably interpret that as (1) the compiler cannot move memory accesses across such a function call, and (2) after calling such a function in one thread, the prior actions to memory from that thread will be visible to another thread after it calls such a function. This was a common interpretation, and this is easily accomplished by treating the functions as opaque and potentially clobbering all of memory.
As an example of problems with this loose specification, the compiler is still allowed to introduce or remove memory accesses (e.g. through register promotion and spillage) and to make larger accesses than necessary (e.g. touching adjacent fields in a struct). Therefore, the compiler completely correctly could "introduce" data races that weren't written in the source code directly. The C++11 memory model stops it from doing so.
C++ says, with regard to mutex lock:
Synchronization: Prior unlock() operations on the same object shall synchronize with this operation.
So C++ is a little more specific. You have to lock and unlock the same mutex to have synchronization. But given this, C++ says that operations before the unlock are visible to the new locker:
An evaluation A strongly happens before an evaluation D if ... there are evaluations B and C such that A is sequenced before B, B simply happens before C, and C is sequenced before D. [ Note: Informally, if A strongly happens before B, then A appears to be evaluated before B in all contexts. Strongly happens before excludes consume operations. — end note ]
(With B = unlock, C = lock, B simply happens before C because B synchronizes with C. Sequenced before is a concept in a single thread of execution, so for example, one full expression is sequenced before the next.)
So, if you restrict yourself to the sorts of primitives (locks, condition variables, ...) that exist in pthread, and to the type of guarantees provided by pthread (sequential consistency), C++ should add no surprises. In fact, it removes some surprises, adds precision, and is more amenable to correctness proofs.
The article Foundations of the C++ Concurrency Memory Model is a great, expository read for anyone interested in this topic about the problems with the status quo at the time and the choices made to fix them in the C++11 memory model.
Edited to more clearly state that the premise of the question is flawed, that reasoning is easier with the memory model, and add a reference to the Boehm paper, which also shaped some of the exposition.
My understanding is that std::mutex lock and unlock have a acquire/release semantics which will prevent instructions between them from being moved outside.
So acquire/release should disable both compiler and CPU reorder instructions.
My question is that I take a look at GCC5.1 code base and don't see anything special in std::mutex::lock/unlock to prevent compiler reordering codes.
I find a potential answer in does-pthread-mutex-lock-have-happens-before-semantics which indicates a mail that says a external function call act as compiler memory fences.
Is it always true? And where is the standard?
Threads are a fairly complicated, low-level feature. Historically, there was no standard C thread functionality, and instead it was done differently on different OS's. Today there is mainly the POSIX threads standard, which has been implemented in Linux and BSD, and now by extension OS X, and there are Windows threads, starting with Win32 and on. Potentially, there could be other systems besides these.
GCC doesn't directly contain a POSIX threads implementation, instead it may be a client of libpthread on a linux system. When you build GCC from source, you have to configure and build separately a number of ancillary libraries, supporting things like big numbers and threads. That is the point at which you select how threading will be done. If you do it the standard way on linux, you will have an implementation of std::thread in terms of pthreads.
On windows, starting with MSVC C++11 compliance, the MSVC devs implemented std::thread in terms of the native windows threads interface.
It's the OS's job to ensure that the concurrency locks provided by their API actually works -- std::thread is meant to be a cross-platform interface to such a primitive.
The situation may be more complicated for more exotic platforms / cross-compiling etc. For instance, in MinGW project (gcc for windows) -- historically, you have the option to build MinGW gcc using either a port of pthreads to windows, or using a native win32 based threading model. If you don't configure this when you build, you may end up with a C++11 compiler which doesn't support std::thread or std::mutex. See this question for more details. MinGW error: ‘thread’ is not a member of ‘std’
Now, to answer your question more directly. When a mutex is engaged, at the lowest level, this involves some call into libpthreads or some win32 API.
pthread_lock_mutex();
do_some_stuff();
pthread_unlock_mutex();
(The pthread_lock_mutex and pthread_unlock_mutex correspond to the implementations of lock and unlock of std::mutex on your platform, and in idiomatic C++11 code, these are in turn called in the ctor and dtor of std::unique_lock for instance if you are using that.)
Generally, the optimizer cannot reorder these unless it is sure that pthread_lock_mutex() has no side-effects that can change the observable behavior of do_some_stuff().
To my knowledge, the mechanism the compiler has for doing this is ultimately the same as what it uses for estimating the potential side-effects of calls to any other external library.
If there is some resource
int resource;
which is in contention among various threads, it means that there is some function body
void compete_for_resource();
and a function pointer to this is at some earlier point passed to pthread_create... in your program in order to initiate another thread. (This would presumably be in the implementation of the ctor of std::thread.) At this point, the compiler can see that any call into libpthread can potentially call compete_for_resource and touch any memory that that function touches. (From the compiler's point of view libpthread is a black box -- it is some .dll / .so and it can't make assumptions about what exactly it does.)
In particular, the call pthread_lock_mutex(); potentially has side-effects for resource, so it cannot be re-ordered against do_some_stuff().
If you never actually spawn any other threads, then to my knowledge, do_some_stuff(); could be reordered outside of the mutex lock. Since, then libpthread doesn't have any access to resource, it's just a private variable in your source and isn't shared with the external library even indirectly, and the compiler can see that.
All of these questions stem from the rules for compiler reordering. One of the fundamental rules for reordering is that the compiler must prove that the reorder does not change the result of the program. In the case of std::mutex, the exact meaning of that phrase is specified in a block of about 10 pages of legaleese, but the general intuitive sense of "doesn't change the result of the program" holds. If you had a guarantee about which operation came first, according to the specification, no compiler is allowed to reorder in a way which violates that guarantee.
This is why people often claim that a "function call acts as a memory barrier." If the compiler cannot deep-inspect the function, it cannot prove that the function didn't have a hidden barrier or atomic operation inside of it, thus it must treat that function as though it was a barrier.
There is, of course, the case where the compiler can inspect the function, such as the case of inline functions or link time optimizations. In these cases, one cannot rely on a function call to act as a barrier, because the compiler may indeed have enough information to prove the rewrite behaves the same as the original.
In the case of mutexes, even such advanced optimization cannot take place. The only way to reorder around the mutex lock/unlock function calls is to have deep-inspected the functions and proven there are no barriers or atomic operations to deal with. If it can't inspect every sub-call and sub-sub-call of that lock/unlock function, it can't prove it is safe to reorder. If it indeed can do this inspection, it would see that every mutex implementation contains something which cannot be reordered around (indeed, this is part of the definition of a valid mutex implementation). Thus, even in that extreme case, the compiler is still forbidden from optimizing.
EDIT: For completeness, I would like to point out that these rules were introduced in C++11. C++98 and C++03 reordering rules only prohibited changes that affected the result of the current thread. Such a guarantee is not strong enough to develop multithreading primitives like mutexes.
To deal with this, multithreading APIs like pthreads developed their own rules. from the Pthreads specification section 4.11:
Applications shall ensure that access to any memory location by more
than one thread of control (threads or processes) is restricted such
that no thread of control can read or modify a memory location while
another thread of control may be modifying it. Such access is
restricted using functions that synchronize thread execution and also
synchronize memory with respect to other threads. The following
functions synchronize memory with respect to other threads
It then lists a few dozen functions which synchronize memory, including pthread_mutex_lock and pthread_mutex_unlock.
A compiler which wishes to support the pthreads library must implement something to support this cross-thread memory synchronization, even though the C++ specification didn't say anything about it. Fortunately, any compiler where you want to do multithreading was developed with the recognition that such guarantees are fundamental to all multithreading, so every compiler that supports multithreading has it!
In the case of gcc, it did so without any special notes on the pthreads function calls because gcc would effectively create a barrier around every external function call (because it couldn't prove that no synchronization existed inside that function call). If gcc were to ever change that, they would also have to change their pthreads headers to include any extra verbage needed to mark the pthreads functions as synchronizing memory.
All of that, of course, is compiler specific. There were no standards answers to this question until C++11 came along with its new memory model.
NOTE: I am no expert in this area and my knowledge about it is in a spaghetti like condition. So take the answer with a grain of salt.
NOTE-2: This might not be the answer that OP is expecting. But here are my 2 cents anyways if it helps:
My question is that I take a look at GCC5.1 code base and don't see
anything special in std::mutex::lock/unlock to prevent compiler
reordering codes.
g++ using pthread library. std::mutex is just a thin wrapper around pthread_mutex. So, you will have to actually go and have a look at pthread's mutex implementation.
If you go bit deeper into the pthread implementation (which you can find here), you will see that it uses atomic instructions along with futex calls.
Two minor things to remember here:
1. The atomic instructions do use barriers.
2. Any function call is equivalent to full barrier. Do not remember from where I read it.
3. mutex calls may put the thread to sleep and cause context switch.
Now, as far as reordering goes, one of the things that needs to be guaranteed is that, no instruction after lock and before unlock should be reordered to before lock or after unlock. This I believe is not a full-barrier, but rather just acquire and release barrier respectively. But, this is again platform dependent, x86 provides sequential consistency by default whereas ARM provides a weaker ordering guarantee.
I strongly recommend this blog series:
http://preshing.com/archives/
It explains lots of lower level stuff in easy to understand language. Guess, I have to read it once again :)
UPDATE:: Unable to comment on #Cort Ammons answer due to length
#Kane I am not sure about this, but people in general write barriers for processor level which takes care of compiler level barriers as well. The same is not true for compiler builtin barriers.
Now, since the pthread_*lock* functions definitions are not present in the translation unit where you are making use of it (this is doubtful), calling lock - unlock should provide you with full memory barrier. The pthread implementation for the platform makes use of atomic instructions to block any other thread from accessing the memory locations after the lock or before unlock. Now since only one thread is executing the critical portion of the code it is ensured that any reordering within that will not change the expected behaviour as mentioned in above comment.
Atomics is pretty tough to understand and to get right, so, what I have written above is from my understanding. Would be very glad to know if my understanding is wrong here.
So acquire/release should disable both compiler and CPU reorder instructions.
By definition anything that prevents CPU reordering by speculative execution prevents compiler reordering. That's the definition of language semantics, even without MT (multi-threading) in the language, so you will be safe from reordering on old compilers that don't support MT.
But these compilers aren't safe for MT for a bunch of reasons, from the lack of thread protection around runtime initialization of static variables to the implicitly modified global variables like errno, etc.
Also, in C/C++, any call to a function that is purely external (that is: not inline, available for inlining at any point), without annotation explaining what it does (like the "pure function" attribute of some popular compiler), must be assumed to do anything that legal C/C++ code can do. No non trivial reordering would be possible (any reordering that is visible is non trivial).
Any correct implementation of locks on systems with multiple units of execution that don't simulate a global order on assembly instructions will require memory barriers and will prevent reordering.
An implementation of locks on a linearly executing CPU, with only one unit of execution (or where all threads are bound on the same unit of execution), might use only volatile variables for synchronisation and that is unsafe as volatile reads resp. writes do not provide any guarantee of acquire resp. release of any other data (contrast Java). Some kind of compiler barrier would be needed, like a strongly external function call, or some asm (""/*nothing*/) (which is compiler specific and even compiler version specific).
I have seen people/articles/SO posts who say they have designed their own "lock-free" container for multithreaded usage. Assuming they haven't used a performance-hitting modulus trick (i.e. each thread can only insert based upon some modulo) how can data structures be multi-threaded but also lock-free???
This question is intended towards C and C++.
The key in lock-free programming is to use hardware-intrinsic atomic operations.
As a matter of fact, even locks themselves must use those atomic operations!
But the difference between locked and lock-free programming is that a lock-free program can never be stalled entirely by any single thread. By contrast, if in a locking program one thread acquires a lock and then gets suspended indefinitely, the entire program is blocked and cannot make progress. By contrast, a lock-free program can make progress even if individual threads are suspended indefinitely.
Here's a simple example: A concurrent counter increment. We present two versions which are both "thread-safe", i.e. which can be called multiple times concurrently. First the locked version:
int counter = 0;
std::mutex counter_mutex;
void increment_with_lock()
{
std::lock_guard<std::mutex> _(counter_mutex);
++counter;
}
Now the lock-free version:
std::atomic<int> counter(0);
void increment_lockfree()
{
++counter;
}
Now imagine hundreds of thread all call the increment_* function concurrently. In the locked version, no thread can make progress until the lock-holding thread unlocks the mutex. By contrast, in the lock-free version, all threads can make progress. If a thread is held up, it just won't do its share of the work, but everyone else gets to get on with their work.
It is worth noting that in general lock-free programming trades throughput and mean latency throughput for predictable latency. That is, a lock-free program will usually get less done than a corresponding locking program if there is not too much contention (since atomic operations are slow and affect a lot of the rest of the system), but it guarantees to never produce unpredictably large latencies.
For locks, the idea is that you acquire a lock and then do your work knowing that nobody else can interfere, then release the lock.
For "lock-free", the idea is that you do your work somewhere else and then attempt to atomically commit this work to "visible state", and retry if you fail.
The problems with "lock-free" are that:
it's hard to design a lock-free algorithm for something that isn't trivial. This is because there's only so many ways to do the "atomically commit" part (often relying on an atomic "compare and swap" that replaces a pointer with a different pointer).
if there's contention, it performs worse than locks because you're repeatedly doing work that gets discarded/retried
it's virtually impossible to design a lock-free algorithm that is both correct and "fair". This means that (under contention) some tasks can be lucky (and repeatedly commit their work and make progress) and some can be very unlucky (and repeatedly fail and retry).
The combination of these things mean that it's only good for relatively simple things under low contention.
Researchers have designed things like lock-free linked lists (and FIFO/FILO queues) and some lock-free trees. I don't think there's anything more complex than those. For how these things work, because it's hard it's complicated. The most sane approach would be to determine what type of data structure you're interested in, then search the web for relevant research into lock-free algorithms for that data structure.
Also note that there is something called "block free", which is like lock-free except that you know you can always commit the work and never need to retry. It's even harder to design a block-free algorithm, but contention doesn't matter so the other 2 problems with lock-free disappear. Note: the "concurrent counter" example in Kerrek SB's answer is not lock free at all, but is actually block free.
The idea of "lock free" is not really not having any lock, the idea is to minimize the number of locks and/or critical sections, by using some techniques that allow us not to use locks for most operations.
It can be achieved using optimistic design or transactional memory, where you do not lock the data for all operations, but only on some certain points (when doing the transaction in transactional memory, or when you need to roll-back in optimistic design).
Other alternatives are based on atomic implementations of some commands, such as CAS (Compare And Swap), that even allows us to solve the consensus problem given an implementation of it. By doing swap on references (and no thread is working on the common data), the CAS mechanism allows us to easily implement a lock-free optimistic design (swapping to the new data if and only if no one have changed it already, and this is done atomically).
However, to implement the underlying mechanism to one of these - some locking will most likely be used, but the amount of time the data will be locked is (supposed) to be kept to minimum, if these techniques are used correctly.
The new C and C++ standards (C11 and C++11) introduced threads, and thread shared atomic data types and operations. An atomic operation gives guarantees for operations that run into a race between two threads. Once a thread returns from such an operation, it can be sure that the operation has gone through in its entirety.
Typical processor support for such atomic operations exists on modern processors for compare and swap (CAS) or atomic increments.
Additionally to being atomic, data type can have the "lock-free" property. This should perhaps have been coined "stateless", since this property implies that an operation on such a type will never leave the object in an intermediate state, even when it is interrupted by an interrupt handler or a read of another thread falls in the middle of an update.
Several atomic types may (or may not) be lock-free, there are macros to test for that property. There is always one type that is guaranteed to be lock free, namely atomic_flag.
I wanted to understand what does one mean by lock_free property of atomic variables in c++11. I did googled out and saw the other relevant questions on this forum but still having partial understanding. Appreciate if someone can explain it end-to-end and in simple way.
It's probably easiest to start by talking about what would happen if it was not lock-free.
The most obvious way to handle most atomic tasks is by locking. For example, to ensure that only one thread writes to a variable at a time, you can protect it with a mutex. Any code that's going to write to the variable needs obtain the mutex before doing the write (and release it afterwards). Only one thread can own the mutex at a time, so as long as all the threads follow the protocol, no more than one can write at any given time.
If you're not careful, however, this can be open to deadlock. For example, let's assume you need to write to two different variables (each protected by a mutex) as an atomic operation -- i.e., you need to ensure that when you write to one, you also write to the other). In such a case, if you aren't careful, you can cause a deadlock. For example, let's call the two mutexes A and B. Thread 1 obtains mutex A, then tries to get mutex B. At the same time, thread 2 obtains mutex B, and then tries to get mutex A. Since each is holding one mutex, neither can obtain both, and neither can progress toward its goal.
There are various strategies to avoid them (e.g., all threads always try to obtain the mutexes in the same order, or upon failure to obtain a mutex within a reasonable period of time, each thread releases the mutex it holds, waits some random amount of time, and then tries again).
With lock-free programming, however, we (obviously enough) don't use locks. This means that a deadlock like above simply cannot happen. When done properly, you can guarantee that all threads continuously progress toward their goal. Contrary to popular belief, it does not mean the code will necessarily run any faster than well written code using locks. It does, however, mean that deadlocks like the above (and some other types of problems like livelocks and some types of race conditions) are eliminated.
Now, as to exactly how you do that: the answer is short and simple: it varies -- widely. In a lot of cases, you're looking at specific hardware support for doing certain specific operations atomically. Your code either uses those directly, or extends them to give higher level operations that are still atomic and lock free. It's even possible (though only rarely practical) to implement lock-free atomic operations without hardware support (but given its impracticality, I'll pass on trying to go into more detail about it, at least for now).
Jerry already mentioned common correctness problems with locks, i.e. they're hard to understand and program correctly.
Another danger with locks is that you lose determinism regarding your execution time: if a thread that has acquired a lock gets delayed (e.g. descheduled by the operating system, or "swapped out"), then it is possible that the entire program is delayed because it is waiting for the lock. By contrast, a lock-free algorithm is always guaranteed to make some progress, even if any number of threads are held up somewhere else.
By and large, lock-free programming is often slower (sometimes significantly so) than locked programming using non-atomic operations, because atomic operations cause a significant hit on caching and pipelining; however, it offers determinism and upper bounds on latency (at least overall latency of your process; as #J99 observed, individual threads may still be starved as long as enough other threads are making progress). Your program may get a lot slower, but it never locks up entirely and always makes some progress.
The very nature of hardware architectures allows for certain small operations to be intrinsically atomic. In fact, this is a very necessity of any hardware that supports multitasking and multithreading. At the very heart of any synchronisation primitive, such as a mutex, you need some sort of atomic instruction that guarantees correct locking behaviour.
So, with that in mind, we now know that it is possible for certain types like booleans and machine-sized integers to be loaded, stored and exchanged atomically. Thus when we wrap such a type into an std::atomic template, we can expect that the resulting data type will indeed offer load, store and exchange operations that do not use locks. By contrast, your library implementation is always allowed to implement an atomic Foo as an ordinary Foo guarded by a lock.
To test whether an atomic object is lock-free, you can use the is_lock_free member function. Additionally, there are ATOMIC_*_LOCK_FREE macros that tell you whether atomic primitive types potentially have a lock-free instantiation. If you are writing concurrent algorithms that you want to be lock-free, you should thus include an assertion that your atomic objects are indeed lock-free, or a static assertion on the macro to have value 2 (meaning that every object of the corresponding type is always lock-free).
Lock-free is one of the non-blocking techniques. For an algorithm, it involves a global progress property: whenever a thread of the program is active, it can make a forward step in its action, for itself or eventually for the other.
Lock-free algorithms are supposed to have a better behavior under heavy contentions where threads acting on a shared resources may spent a lot of time waiting for their next active time slice. They are also almost mandatory in context where you can't lock, like interrupt handlers.
Implementations of lock-free algorithms almost always rely on Compare-and-Swap (some may used things like ll/sc) and strategy where visible modification can be simplified to one value (mostly pointer) change, making it a linearization point, and looping over this modification if the value has change. Most of the time, these algorithms try to complete jobs of other threads when possible. A good example is the lock-free queue of Micheal&Scott (http://www.cs.rochester.edu/research/synchronization/pseudocode/queues.html).
For lower-level instructions like Compare-and-Swap, it means that the implementation (probably the micro-code of the corresponding instruction) is wait-free (see http://www.diku.dk/OLD/undervisning/2005f/dat-os/skrifter/lockfree.pdf)
For the sake of completeness, wait-free algorithm enforces progression for each threads: each operations are guaranteed to terminate in a finite number of steps.