pthread rwlock lock/unlock from different threads - multithreading

The docs says that locking from a thread and unlocking from another a rwlock results in undefined behaviour. I have an array and two threads, one allocating it and one deallocating it, this happens in a cycle, and there are also some threads reading/writing in it, but they never overlap so no synchronization is needed there. The problem is the read/write threads still try to use the array in the timeframe between dealloc - alloc. I was thinking of using a read lock for the read/write threads and lock the array for writing in the dealloc thread and unlocking writing in alloc thread. But this results in undefined behavior since they happen on different threads. What would be the right approach in this case?

You need some variable that stores the state. You can protect that variable with a lock. So when a thread needs to check or change the state, it acquires the lock, checks or changes the state, and then releases the lock.

Related

linux unnamed posix semaphore sem_destroy, sem_wait method question

when there are waiting semaphores of sem_wait method, I call the sem_destroy method on other thread. But waiting semaphore was not wake up.
In case of mutex, pthread_mutex_destroy was return the value EBUSY when there are some waiting threads.
however sem_destroy return 0 and errno was also set 0.
I want to destroy semaphore after calling sem_destroy to block access as destroyed semaphore and to wake up the waiting thread.
Semaphore handle of Window OS is possible.
please advise me. thank you.
POSIX says this about sem_destroy:
The effect of destroying a semaphore upon which other threads are currently blocked is undefined.
It specifically doesn't say that other threads are woken up. In fact, if sem_t contains a pointer to memory, what it almost certainly does do is free the memory, meaning you then have a use-after-free security problem. (Whether that is the case depends on your libc.)
The general approach of allocation for mutexes and semaphores is that they should be either allocated and freed with their relevant data structure, or they should be allocated before the relevant code needs them and then freed after the entire code is done with them. In C, you cannot safely deallocate data structures (e.g., with sem_destroy) that are in use.
If you want to wake up all users of the semaphore, you must increment it until all users have awoken. You can call sem_getvalue to determine if anyone is waiting on the semaphore and then call sem_post to increment it. Only then can you safely destroy it. Note that this can have a race condition, depending on your code.
However, note that you must be careful that the other code does not continue to use the semaphore after it's destroyed, such as by trying to re-acquire it in a loop. If you are careful to structure your code properly, then you can have confidence that this won't happen.

Kernel Programming - Mutexes

So I'm trying to use mutex_init(), mutex_lock(), mutex_unlock() for thread synchronization.
I am currently trying to schedule threads in a round robin fashion(but more than 1 thread could be running at a time) and I set the current state of a thread to TASK_INTERRUPTIBLE, followed by waking up another thread whose PID, I have in a list.
I need to iterate over this list for my logic.
As I understand it, I need to lock this list as I access its elements, or another thread might miss a new entry while I'm making changes to it. Also, as one mutex has locked a resource, no other mutex can unlock it, until the original mutex releases it.
But, I'm still not sure if I'm locking it correctly. (I release the lock before I call schedule(), and re-lock after that)
I declare a mutex locally within a thread and lock the list. After my current thread locks
mutex_lock(&lock);
and I iterate over the list, till I find something(or ends if it doesn't find anything), then unlocks.
mutex_unlock(&lock);
I assume locking while I iterate is legal. I have never seen examples of this though.
Also, is it normal for the process to have a state of (TASK_UNINTERRUPTIBLE) while it holds a mutex lock?
EDIT : I am adding some more information based on the answer below.
It is possible my program may be run on a virtual machine with a single core. Therefore, I do not want to risk infinite polling using spin_lock().
I am trying to maintain scheduling between threads that have a certain id. For example if there are 4 threads. 2 in set 'A' and 2 in set 'B'. I allow only 1 thread to run in each set. But I switch between threads in a given set. However, a thread in set 'A' should not switch to any thread in set 'B'
(I know the kernel scheduler wont be perfect, so an approximate switching will do).
My Reasoning for TASK_STATE's:
1) Initial thread that gets created is running.
2) If another thread in the same set is running (and this one hasn't executed for a given time). Set other thread to TASK_INTERRUPTIPLE, while calling schedule(); Note: There can be more than 2 threads in each set, but let's keep it simple by considering only 2 for now.
3) If it has executed for enough time, set this task to TASK_INTERRUPTIPLE, set the other task in the same set to TASK_RUNNING, while calling schedule();
All this logic happens while I am accessing certain data structures which are locked by a (now) Global Mutex. I unlock the mutex just before I call schedule(), and instantly re-lock afterward. After my logic part is done, I completely unlock the mutex.
Is there anything fundamentally wrong with the approach?
As I understand it, I need to lock this list as I access its elements
Yes, that is true. But if you use a mutex, you're going to be really sad because a call to lock/unlock is a call to the scheduler. Therefore, calling it from inside the scheduler should result in deadlock. What you need to do depends on if your processor is multi-core or (the mythical) single-core. (Is this a virtual system?) On a single-core processor you can disable interrupts. On a multi-core processor, disabling interrupts is not sufficient (it only disables interrupts for that one core, and another core may still be interrupted). The simplest thing to do on a multi-core is to use a spinlock. Unlike the mutex, both of these locking mechanisms can be unlocked from different threads.
I set the current state of a thread to TASK_INTERRUPTIBLE
Is the thread being taken off the CPU? If so, it's not running, so I suspect that TASK_INTERRUPTIBLE is the wrong state. It would be helpful if you could list the possible states for me or if you could describe what the state is supposed to indicate. Because to me "TASK_INTERRUPTIBLE" sounds like a running task.
I declare a mutex locally within a thread and lock the list
Local mutexes are a red flag! The resource you are locking should be protected by a mutex with the same scope. If the list is global, it should have a global mutex to protect it. Threads that want to use the list must first acquire its mutex. Of course, as I already talked about, you probably want to use a different kind of locking to protect the list of ready-to-run processes.
I assume locking while I iterate is legal
It is perfectly legal (assuming of course that your mutual exclusion scheme is bug-free). In fact, it's required. If another thread were allowed to, for example, remove a node from the list while you were reading it, you could end up dereferencing a deleted node.
Also, is it normal for the process to have a state of TASK_UNINTERRUPTIBLE while it holds a mutex lock?
No, not while it holds the lock if the process is currently running on a CPU. A mutex is available to user code. If holding a mutex made the process uninterruptible, that would mean that a process could hijack the system by simply locking a mutex and never releasing it. Now, you will find that the lock and unlock functions need to be uninterruptible on a single-core processor. However, it doesn't make sense to set the state for the process because it's actually the scheduler that must not be interrupted.

How does a Mutex work? Does a mutex protect variables globally? Does the scope in which it is defined matter?

Does a mutex lock access to variables globally, or just those in the same scope as the locked mutex?
Note that I had to change the title of this question, as a lot of answers seem to be confused as to what I was asking. This is not a question about the scope (global or otherwise) of a "mutex object", it is a question about what scope of variables are "locked" by a mutex.
I believe the answer to be that a mutex locks access to all variables, ie; all global and locally scoped variables. (This is a result of a mutex blocking thread execution rather than access to specific regions of memory.)
I am attempting to understand Mutexes.
I was attempting to understand what sections of memory, or equivalently, which variables, a mutex would lock.
However my understanding from reading around online is that Mutexes do not lock memory, they lock (or block) simultaneously running threads which are all members of the same process. (Is that correct?)
https://mortoray.com/2011/12/16/how-does-a-mutex-work-what-does-it-cost/
So my question has become simply "are mutexes global?"
... or are they perhaps "generally speaking global, but the stackoverflow community can imagine some special cases in which they are not?"
When originally considering my question, I was interested in things such as those shown in the following example.
// both in global scope, this mutex will lock any global scope variable?
int global_variable;
mutex global_variable_mutex;
int main()
{
// one thread operates here and locks global_variable_mutex
// before reading/writing
{
// local variables in a loop
// launch some threads here, and wait later
int local_variable;
mutex local_variable_mutex;
// wait for launched thread to return
// does the mutex here prevent data races to the variable
// global_variable ???
}
}
One may assume this is pseudo-code for C++ or C, or any other similarly relevant language.
2021 edit: Question title has been changed to better reflect the contents of the question and associated answers.
So my question has become simply "are mutexes global?"
No. A mutex has a lock() and an unlock() method, and the only thing a mutex does is cause its lock() call (from any thread) not to return for as long as another thread has that mutex locked. When the thread that was holding the mutex locked calls unlock(), that is when the lock() call will return in the first thread. That way it is guaranteed that only a single thread will be holding the mutex-lock (i.e. executing in the region between its lock() call and its unlock() call) at any given time.
That's really all there is to it. So a mutex will effect only the threads that call lock() on that particular mutex, and nothing else.
Mutex stands for "Mutual Exclusion" - using one correctly ensures that only one thread at a time will ever be executing any "critical section" protected by the same mutex.
If there are some variables you only ever modify inside critical sections protected by the same mutex, your code doesn't have a data race. No matter whether they're global, static, or pointed to by different variables in different threads or any other way two threads might have a reference to the same object.
When I asked this question I was confused...
When I originally asked this question, I was confused because I had no conceputal understanding of how a "mutex" functions in hardware, whereas I did have a conceptual understanding of many other things that exist in hardware. (For example, how a compiler converts text into machine readable instructions. How cache and memory work. How graphics or coprocessors work. How network hardware and interfaces work, etc.)
Misconception 1: Mutex does not lock memory locations
When I first heard about Mutex, long before writing this question, I misunderstood a mutex to be a feature which locks regions of memory. (That region might be global.)
This is not what happens. Other threads and processes can continue to access main memory and cache if another thread locks a mutex. You can see immediatly why such a design would be inefficient, since it would block all other system processes, for the sake of synchronizing one.
Misconception 2: The scope in which a mutex object is declared is irrelevant
The context of this is C code, and C like languages where you have scoped blocks defined by { and } however the same logic could apply to Python where scope is defined by indentation.
I believe that this misunderstanding came from the existance of scoped_lock objects, and similar concepts where scope is used to manage the lifetime (locking and unlocking, resources) of a Mutex object.
One could also argue that since pointers and references to a Mutex can be passed around a program, the scope of a Mutex couldn't be used to define what variables are "locked" by a mutex.
For example, I misunderstood the following snippet:
{
int x, y, z;
Mutex m;
m.lock();
}
I believed that the above snippet would lock access to variables x, y and z from all other threads because x, y and z are declared in the same scope as the mutex m. This is also not how a mutex works.
Understanding 1: Mutex is typically implemented in hardware using atomic operations
Atomic operations are completely seperate from the concept of mutex, however they are a prerequisite to understanding how a mutex can exist, and how it can work.
When a CPU executes something like c = a + b, this involves a sequence of individual (atomic) operations. The word Atom is derived from Atomos meaning "indivisible", or "fundamental". (Atoms are divisible, but when theorists of Ancient Greece originally concieved of the objects from which matter was composed, they assumed that particles must be divisible down to some fundamental smallest possible component, which itself is indivisible. They were not too far wrong, since an atom is made from other fundamental particles which so far we understand to be indivisible.)
Returning to the point: c = a + b is something like the following:
load a from memory into register 1
load b from memory into register 2
do operation add: add contents of register 2 to register 1, result is in register 1
save register 1 to memory c
The add operation might take several clock cycles, and loading/saving to memory takes typically of order 100 clock cycles on modern x86 machines. However each operation is atomic in the sense that a single CPU instruction is being completed, and this instruction cannot be divided into any smaller step of smaller instructions. The instructions are themselves fundamental computing operations.
With that understood, there exists a set of atomic instructions which can do things such as:
load a value from memory increment it and save it to memory
load a value from memory decrement it and save it to memory
load a value from memory, compare it to a value which is already loaded into a register, and branch depending on the comparison result
Note that such operations are typically significantly slower than their non-atomic sequence counterparts. This is because optimizations such as pipelining are forfit when executing the above instructions. (I think?)
At this point my knowledge becomes a bit less accurate and more hand-wavey, but as far as I understand, these operations are typically implemented by having some digital logic inside the processor which blocks all other processes from running while these atomic operations (listed above) are executing.
Meaning: If there are 8 CPU cores running, if one core encounters an instruction like the above, it signals the other cores to stop running until it has finished that atomic operation. (It is at least something approximatly along these lines.)
Understanding 2: Actual mutex operation
Given the above, it is possible to implement a mutex using these atomic machine instructions. Other answers posted here suggest possible ways of doing it including something similar to reference counting. (Semaphore.)
How an acutal mutex in C++ works is this:
Each mutex object has a variable in memory associated with it, the value of this variable indicates whether a mutex is locked or not
This mutex variable is updated using the special atomic operations that a CPU supports for the purpose of allowing a mutex to be programmed
Elsewhere in memory there are some other variables/data which you want to protect/synchronize access to
This synchronization is done using the mutex variable/data
Before a thread reads/writes to some data/variable which needs to be accessed mutually exclusively by all threads which operate on it, that thread must first "lock" the special mutex data/variable
This is done using the atomic operations built into a CPU for the purpose of supporting mutex programming
So you see, the data which is "locked" and accessed mutually exclusively is entirely independent from the actual data used to store the state of the mutex.
If another thread wants to read/write the data which must be accessed mutually exclusively, it will try to lock the mutex. If the mutex is already locked, that means another thread has the right to access this data, and no other thread is permitted to, therefore this thread will typically go to sleep, and will be re-woken by the operating system when the mutex is next unlocked.
It is important to note the operating system thread (kernel) is critically involved in the mutex process. Typically, before a thread sleeps, it will tell the operating sytem that it wishes to be woken up again when the mutex is free. The operating system is also notified when other threads lock or unlock a mutex. Hence synchronization of information about the state of a mutex is passed via messages through the operating system kernel.
This is why writing a multiple thread OS kernel is (proabably) impossible (if not very difficult). I don't know if this has actually been done successfully. It sounds like a difficult problem which might be the subject of current CS research.
This is pretty much everything I know about the subject. Obviously my knowledge is not absolute...
Note: Feel free to correct my Greek history or x86 Machine Instruction knowledge in the comments section. No doubt not everything here is perfectly accurate.
As your question suggests, I assume you are asking your question independent of any programming language.
First it is important to understand what is a mutex and how it works? A mutex is a binary semaphore. Then what is a semaphore? A semaphore is an integer with following attributes,
You can initialize it into any permitted value (For a mutex, it is 1 or 0).
A thread can access the semaphore and it can increment or decrement its integer value.
When a thread decrements it,
If the result is positive or zero, that thread can continue its process.
If the result is negative, that thread will be waiting and the semaphore value will not be further decremented by any later thread.
If a thread increments it, (in that case semaphore value will be either positive or 0) and the result is 0, one of the waiting threads can continue execution.
So when there's a situation where a thread is trying to access a shared resource it will decrement the mutex value (from 0, so that other thread is waiting). And when it finishes, it will increment the mutex value (So that the waiting thread can continue). That's how the access control happens by means of a mutex (Binary semaphore).
I think you understand that your question is a non-applicable one here. As a simple answer for
So my question has become simply "are mutexes global?"
is simply NO.
A mutex has whatever scope you assign to it. It can be global or local again based on where and how you declare it. If for example you declare a mutex in global memory in a place where you can access it globally, then it is indeed global. If instead you declare it at function or private class scope level, then only that function or class will have access to it.
That said, in order to be useful for synchronization, the mutex needs to be declared in a scope that can be accessed by the threads needing to synchronize on it. Whether that's at global scope or some local scope depends on your program structure. I'd advise declaring it at the highest scope accessible to the threads but no higher.
In your particular example, the mutex is indeed global because you've declared it in global memory.
Locking doesn't operate on the variables it protects, it just works by giving threads a way to arrange that only one thread at a time will be doing something (like reading+writing a data structure). And that it will be finished, with memory effects visible, before the next thread's turn to read and maybe modify that data. (A readers+writers lock allows multiple readers but only one writer).
Any thread that can access the mutex object can lock / unlock it. The mutex object itself is a normal variable that you can put in any scope you want, even a local variable and then put a pointer to it somewhere that other threads can see. (Although normally you wouldn't do that.)
Mutex is named for "Mutual Exclusion" - using one correctly ensures that only one thread at a time will ever be executing any "critical section" (wikipedia) protected by the same mutex. Separate mutexes can allow different threads to hold different locks. Different functions or blocks that use the same mutex (normally because they access the same data) won't both run at once.
If there are some variables you only ever modify inside critical sections protected by the same mutex, those accesses won't be data race, and if you don't have other bugs, your code is thread-safe. No matter whether they're global, static, or pointed to by different variables in different threads or any other way two threads might have a reference to the same object.
If you write code that accesses shared data without taking a lock on a mutex, it might see a partially-updated value, especially for a struct with multiple pointers / integers. (And in C++, simultaneous accesses to non-atomic variables is undefined behaviour if they're not all reads).
Locking is a cooperative activity, normally nothing stops you from getting it wrong. If you're familiar with file locking, you may have heard of advisory vs. mandatory locks (the OS will deny open calls by other programs). Mutexes in multi-threaded programs are advisory; no memory protection or other hardware mechanism stops another thread from executing code that accesses the bytes of an object.
(At a low enough level, that's actually useful for lock-free atomics, especially with some control over ordering of those operations from memory barriers and/or release-store / acquire-load. And CPU cache hardware is up to the task of maintaining coherency from multiple accesses. But if you use locking, you don't have to worry about any of that. If you use locking incorrectly, understanding the possible symptoms might help identify that there is a locking problem.)
Some programs have phases where only a single thread is running, or only one that would need to touch certain variables, so enforced locking for every access to a variable isn't something that every language provides. (C++ std::atomic<T> is sort of like that; every access is as-if there was a lock/unlock of a lock protecting just that T object, except it's limited to operations that most CPUs can do without needing to lock/unlock a separate lock. Unless you use a large T, then there actually is a lock. Or if you use a memory order weaker than the default seq_cst, you can see orderings that wouldn't have been possible if all accesses acquiring/releasing locks.)
Besides, consistency between multiple variables is often important, so it matters that you hold one lock across multiple operations on multiple variables, or multiple members of the same struct.
Some tools can help detect code that doesn't respect a mutex while other threads are running, though, like clang -fsanitize=thread.

Know how many are waiting on a pthread mutex lock

I would like to know how many threads are waiting on a lock so I would be able to destroy it safely.
The problem is that I can't destroy the lock when someone holds it or someone is waiting on it.
My program can make sure that no new requests are made to acquire the lock, but how can I know when all the threads that waited on it are done with it?
I thought about a conditional variable but I suspect it will create problems..
dlv, could you add some code snippet to your description.
I hope you should be using condition variables,
Each thread will block in pthread_cond_wait() until the other thread signals it to wake up. This will not cause a deadlock. It can easily be extended to many threads, by allocating one int, pthread_cond_t and pthread_mutex_t per thread.
pthread_cond_wait() blocks the calling thread until the specified condition is signalled. This routine should be called while mutex is locked, and it will automatically release the mutex while it waits. After signal is received and thread is awakened, mutex will be automatically locked for use by the thread. The programmer is then responsible for unlocking mutex when the thread is finished with it.
The pthread_cond_signal() routine is used to signal (or wake up) another thread which is waiting on the condition variable. It should be called after mutex is locked, and must unlock mutex in order for pthread_cond_wait() routine to complete.
The pthread_cond_broadcast() routine should be used instead of pthread_cond_signal() if more than one thread is in a blocking wait state.
It is a logical error to call pthread_cond_signal() before calling pthread_cond_wait().
Proper locking and unlocking of the associated mutex variable is essential when using these routines. For example:
Failing to lock the mutex before calling pthread_cond_wait() may cause it NOT to block.
Failing to unlock the mutex after calling pthread_cond_signal() may not allow a matching pthread_cond_wait() routine to complete (it will remain blocked).
If threads that can use the mutex still exist or might be created in the future then don't delete it.
You do know and are tracking what threads are created, right?
If, for some reason, you cannot keep track of the threads using a resource, your only way out is to leak the resource. It can never be safely deleted because you never know when you are done using it.
Say you had a counter that counted the threads using a mutex. That counter would need its own mutex. Then how do you decide when to delete that one?
That way of thinking is the road that leads to hell. You could do what you want with condition variables, but the result would be an extremely weak design.
Assuming you managed to create such a monster, it would basically allow you to kill "safely" any other thread regardless of its internal state. Except for a quick and dirty panic exit (in case of some internal software error), this is the worst possible way of solving synchronization issues.
A design relying on such tricks would have to create implicit synchronizations between tasks to make sure the terminations occur in the proper order. A lot of software are designed that way, and most of them allow mediocre programmers to make a living by maintaining the pile of crap they created in the first place.
Task termination should be an issue solved at global design level, not by a toolbox of wonky objects that allow you to twist synchronization any odd way.

Reentrant Locks: pros and cons?

In what situations would one want to use reentrant locks versus normal locks?
The main difference between Simple/Regular Locks and Re-entrant Locks is that simple locks allow one thread to acquire a lock at a given point in time, keeping every other thread waiting, including the thread that holds the lock if it tried to lock again. Re-entrant locks allow the same thread to acquire a lock as many times as needed, provided that they already hold the lock, and keeps all other threads in a waiting queue for the same lock.
Re-entrant Locks are generally useful when recursion is needed. Imagine that you have a recursive function that needs to acquire a lock to execute. If you were using a simple lock, your first thread can easily deadlock itself. First iteration of the recursion will acquire the lock successfully, the second iteration will try to acquire the lock again, but will block forever. The second iteration will wait for the first iteration to unlock, but the first iteration will not unlock unless the second iteration completes.
A re-entrant lock is useful here because once a thread holds the lock, it can lock as many times as it pleases after that. Only catch is that your thread will have to unlock as many times as it locked, making it similar to a counting semaphore.
I presume a reentrant lock would have some additional overhead compared to a normal lock - to check what thread is acquiring the lock.
Therefore, if you know that under normal operation a thread will only acquire the lock once before releasing it again, you may gain some performance by using a normal lock. This could be particularly beneficial in tight loops, etc.

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