Is what I am doing preventing Deadlock? - multithreading

I have 12 resources (r_1, r_2, ..., r_12), and 12 corresponding locks (l_1, l_2, ..., l_12) that my threads try to access. Each thread needs a specific sequence of resources to operate on. For example, thread 1 needs r_1, r_3, and r_5. Thread 2 needs r_1, r_7, r_8, r_10.
Now what I've basically done is ordered the resources from 1 to 12, make each thread lock its required resources in this order (ascending order), then when the thread is done, I unlock them in the reverse order (descending order) to maintain an order.
So my question is, am I preventing a deadlock in this case? Or can there happen a deadlock?

TL;DR: Yes, this system is totally immune to deadlock. At any point in time, the thread holding the highest-numbered lock must be able to make progress, since it cannot be waiting to acquire any locks held by other processes. More formally, your conditions ensure a total ordering on lock acquisition by all processes, which in turn ensures that circular wait can never occur. Circular wait is a necessary precondition for deadlock.
Detail: In order for deadlock to take place, all four of the following conditions must apply (see relevant Wikipedia):
Mutual exclusion - i.e. concurrent processes are accessing unsharable resources. Locks are unsharable by definition (they are also called mutexes for this reason).
Hold and wait - at least one process is attempting to access multiple resources, and it does so by holding some of them and then waiting for the others. This condition probably applies in your case, depending on the exact semantics of your program.
No preemption - it is not possible for processes to have their resources taken from them by other processes. Once again, this is a property of the locks we're using.
Circular wait - there is a cycle of processes, each waiting on a resource held by the next. This condition doesn't apply here. Consider a thread A, waiting on accessing a lock L_i. That lock must be held by a thread B which has already obtained all the locks it requires from indices 1 to i. As a result, B cannot be waiting on A. Similarly, any thread that B is waiting on in order to acquire its next lock L_j (where j > i by the order in which locks are acquired) cannot be waiting on any locks with indices 1 to j. By induction, there can be no cycles of dependency in this system.
In concurrent programming, it is typical for the first three cases to be set by the context in which you are developing (which concurrency primitives are being used etc.), whereas the last can occasionallyâ„¢ be avoided by cleverness.

Related

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.

FreeRTOS Mutex multiple task with same priority

I'm having some problems with FreeRTOS binary mutex. On my aplication there are multiple threads (tasks) with the same priority, two of these access to file I/O functions that are within mutex take and mutex release.
Depending on some timings one task is doing starvation to the other. Is that possible?
FreeRTOS take into account how many time is a task waiting for a resource?
Thanks
Are you using the mutex in tight loops in multiple tasks? If so then there is a logical reason why one task might hold the mutex for longer than you think. If tasks A and B have the same priority, A is holding the mutex and B is waiting for the mutex, then a context switch won't occur when A gives the mutex back because B has the same priority as A (it would occur if B had a higher priority, but it would be a breach of the scheduling algorithm and risk task thrashing if a task switch occurred to an equal priority task). There, if A is in a loop, gives the mutex back, then immediately takes it again, every time B attempts to take the mutex it will find A is still holding the mutex so, if B is also in a loop, it will block on the mutex again. This scenario is easy to fix - but suggest you read the chapter that describes this in the freely available book: http://www.freertos.org/Documentation/RTOS_book.html

Java Thread Live Lock

I have an interesting problem related to Java thread live lock. Here it goes.
There are four global locks - L1,L2,L3,L4
There are four threads - T1, T2, T3, T4
T1 requires locks L1,L2,L3
T2 requires locks L2
T3 required locks L3,L4
T4 requires locks L1,L2
So, the pattern of the problem is - Any of the threads can run and acquire the locks in any order. If any of the thread detects that a lock which it needs is not available, it release all other locks it had previously acquired waits for a fixed time before retrying again. The cycle repeats giving rise to a live lock condition.
So, to solve this problem, I have two solutions in mind
1) Let each thread wait for a random period of time before retrying.
OR,
2) Let each thread acquire all the locks in a particular order ( even if a thread does not require all the
locks)
I am not convinced that these are the only two options available to me. Please advise.
Have all the threads enter a single mutex-protected state-machine whenever they require and release their set of locks. The threads should expose methods that return the set of locks they require to continue and also to signal/wait for a private semaphore signal. The SM should contain a bool for each lock and a 'Waiting' queue/array/vector/list/whatever container to store waiting threads.
If a thread enters the SM mutex to get locks and can immediately get its lock set, it can reset its bool set, exit the mutex and continue on.
If a thread enters the SM mutex and cannot immediately get its lock set, it should add itself to 'Waiting', exit the mutex and wait on its private semaphore.
If a thread enters the SM mutex to release its locks, it sets the lock bools to 'return' its locks and iterates 'Waiting' in an attempt to find a thread that can now run with the set of locks available. If it finds one, it resets the bools appropriately, removes the thread it found from 'Waiting' and signals the 'found' thread semaphore. It then exits the mutex.
You can twiddle with the algorithm that you use to match up the available set lock bools with waiting threads as you wish. Maybe you should release the thread that requires the largest set of matches, or perhaps you would like to 'rotate' the 'Waiting' container elements to reduce starvation. Up to you.
A solution like this requires no polling, (with its performance-sapping CPU use and latency), and no continual aquire/release of multiple locks.
It's much easier to develop such a scheme with an OO design. The methods/member functions to signal/wait the semaphore and return the set of locks needed can usually be stuffed somewhere in the thread class inheritance chain.
Unless there is a good reason (performance wise) not to do so,
I would unify all locks to one lock object.
This is similar to solution 2 you suggested, only more simple in my opinion.
And by the way, not only is this solution more simple and less bug proned,
The performance might be better than solution 1 you suggested.
Personally, I have never heard of Option 1, but I am by no means an expert on multithreading. After thinking about it, it sounds like it will work fine.
However, the standard way to deal with threads and resource locking is somewhat related to Option 2. To prevent deadlocks, resources need to always be acquired in the same order. For example, if you always lock the resources in the same order, you won't have any issues.
Go with 2a) Let each thread acquire all of the locks that it needs (NOT all of the locks) in a particular order; if a thread encounters a lock that isn't available then it releases all of its locks
As long as threads acquire their locks in the same order you can't have deadlock; however, you can still have starvation (a thread might run into a situation where it keeps releasing all of its locks without making forward progress). To ensure that progress is made you can assign priorities to threads (0 = lowest priority, MAX_INT = highest priority) - increase a thread's priority when it has to release its locks, and reduce it to 0 when it acquires all of its locks. Put your waiting threads in a queue, and don't start a lower-priority thread if it needs the same resources as a higher-priority thread - this way you guarantee that the higher-priority threads will eventually acquire all of their locks. Don't implement this thread queue unless you're actually having problems with thread starvation, though, because it's probably less efficient than just letting all of your threads run at once.
You can also simplify things by implementing omer schleifer's condense-all-locks-to-one solution; however, unless threads other than the four you've mentioned are contending for these resources (in which case you'll still need to lock the resources from the external threads), you can more efficiently implement this by removing all locks and putting your threads in a circular queue (so your threads just keep running in the same order).

Is Deadlock recovery possible in MultiThread programming?

Process has some 10 threads and all 10 threads entered DEADLOCK state( assume all are waiting for Mutex variable ).
How can you free process(threads) from DEADLOCK state ? .
Is there any way to kill lower priority thread ?( in Multi process case we can kill lower priority process when all processes in deadlock state).
Can we attach that deadlocked process to the debugger and assign proper value to the Mutex variable ( assume all the threads are waiting on a mutex variable MUT but it is value is 0 and can we assign MUT value to 1 through debugger ) .
If every thread in the app is waiting on every other, and none are set to time out, you're rather screwed. You might be able to run the app in a debugger or something, but locks are generally acquired for a reason -- and manually forcing a mutex to be owned by a thread that didn't legitimately acquire it can cause some big problems (the thread that previously owned it is still going to try and release it, the results of which can be unpredictable if the mutex is unexpectedly yanked away. Could cause an unexpected exception, could cause the mutex to be unlocked while still in use.) Anyway it defeats the whole purpose of mutexes, so you're just covering up a much bigger problem.
There are two common solutions:
Instead of having threads wait forever, set a timeout. This is slightly harder to do in languages like Java that embed mutexes into the language via synchronized or lock blocks, but it's almost always possible. If you time out waiting on the lock, release all the locks/mutexes you had and try later.
Better, but potentially much more complex, is to figure out why everything's fighting for the resource and remove that contention. If you must lock, lock consistently. But if there's 10 threads blocking on a single mutex, that could be a clue either that your operations are badly chunked (ie: that your threads are doing too much or too little at once before trying to acquire a lock), or that there's unnecessary locking going on. Don't lock unless you have to. Some synchronization could be obviated by using collections and algorithms specifically designed to be "lock-free" while still offering thread-safety.
Adding another answer because I don't agree with the solutions proposed by cHao earlier - the analysis is fine.
First, why I disagree with the two solutions offered:
Reduce contention
Contention doesn't lead to deadlocks. It just causes poor performance. Deadlock means no performance whatsoever. Therefore, reducing contention does not solve deadlocks.
timeout on mutex.
A mutex protects a resource, and a thread locks the mutex because it needs the resource. With a timeout, you won't be able to acquire the resource, and your thread fails. Does it solve the deadlock problem? Only if the failing thread releases another resource that was blocking the other threads.
But in that case, there's a much better solution. Mutexes should have a partial ordering. If there is at least one thread that can both mutex A and B, you should decide whether A or B is acquired first, and then stick with that. This must be a transitive order: if you lock A before B, and B before C, then obviously you must lock A before C.
This is a perfect solution to deadlocks. Look back at the timeout example: it only works if the thread that times out waiting on A then releases its lock on B, to release another thread that was waiting on B. In the most simple case, that other thread was itself directly locking A. Thus, the mutexes A and B are not properly ordered. You should have consistently locked either A or B first.
The timeout case could also be the result of a cyclic order problem; one thread locks A then B, another B then C, and a third C then A, with the deadlock happening when each thread owns one lock. The solution again is the same; order the locks.
Alternatively said, mutex lock orders can be described by a directed graph. If a thread locks A before B, there's an arc from A to B. Deadlocks appear if the directed graph is cyclic, and then the arcs of that cycle are the deadlocked threads.
This theory can be a bit complex, but there are some simple insights to be found. For instance, from the graph theory, we know that trees are acyclic graphs. Hence, neither "leaf mutexes" (those that are always locked last) nor "root mutexes" (those that are always locked first) can cause deadlocks. Leaf mutexes are excluded because no thread ever blocks holding them, and root mutexes are excluded because the thread that holds them will be able to lock all subsequent mutexes in due time.

Conditional Variable vs Semaphore

When to use a semaphore and when to use a conditional variable?
Locks are used for mutual exclusion. When you want to ensure that a piece of code is atomic, put a lock around it. You could theoretically use a binary semaphore to do this, but that's a special case.
Semaphores and condition variables build on top of the mutual exclusion provide by locks and are used for providing synchronized access to shared resources. They can be used for similar purposes.
A condition variable is generally used to avoid busy waiting (looping repeatedly while checking a condition) while waiting for a resource to become available. For instance, if you have a thread (or multiple threads) that can't continue onward until a queue is empty, the busy waiting approach would be to just doing something like:
//pseudocode
while(!queue.empty())
{
sleep(1);
}
The problem with this is that you're wasting processor time by having this thread repeatedly check the condition. Why not instead have a synchronization variable that can be signaled to tell the thread that the resource is available?
//pseudocode
syncVar.lock.acquire();
while(!queue.empty())
{
syncVar.wait();
}
//do stuff with queue
syncVar.lock.release();
Presumably, you'll have a thread somewhere else that is pulling things out of the queue. When the queue is empty, it can call syncVar.signal() to wake up a random thread that is sitting asleep on syncVar.wait() (or there's usually also a signalAll() or broadcast() method to wake up all the threads that are waiting).
I generally use synchronization variables like this when I have one or more threads waiting on a single particular condition (e.g. for the queue to be empty).
Semaphores can be used similarly, but I think they're better used when you have a shared resource that can be available and unavailable based on some integer number of available things. Semaphores are good for producer/consumer situations where producers are allocating resources and consumers are consuming them.
Think about if you had a soda vending machine. There's only one soda machine and it's a shared resource. You have one thread that's a vendor (producer) who is responsible for keeping the machine stocked and N threads that are buyers (consumers) who want to get sodas out of the machine. The number of sodas in the machine is the integer value that will drive our semaphore.
Every buyer (consumer) thread that comes to the soda machine calls the semaphore down() method to take a soda. This will grab a soda from the machine and decrement the count of available sodas by 1. If there are sodas available, the code will just keep running past the down() statement without a problem. If no sodas are available, the thread will sleep here waiting to be notified of when soda is made available again (when there are more sodas in the machine).
The vendor (producer) thread would essentially be waiting for the soda machine to be empty. The vendor gets notified when the last soda is taken from the machine (and one or more consumers are potentially waiting to get sodas out). The vendor would restock the soda machine with the semaphore up() method, the available number of sodas would be incremented each time and thereby the waiting consumer threads would get notified that more soda is available.
The wait() and signal() methods of a synchronization variable tend to be hidden within the down() and up() operations of the semaphore.
Certainly there's overlap between the two choices. There are many scenarios where a semaphore or a condition variable (or set of condition variables) could both serve your purposes. Both semaphores and condition variables are associated with a lock object that they use to maintain mutual exclusion, but then they provide extra functionality on top of the lock for synchronizing thread execution. It's mostly up to you to figure out which one makes the most sense for your situation.
That's not necessarily the most technical description, but that's how it makes sense in my head.
Let's reveal what's under the hood.
Conditional variable is essentially a wait-queue, that supports blocking-wait and wakeup operations, i.e. you can put a thread into the wait-queue and set its state to BLOCK, and get a thread out from it and set its state to READY.
Note that to use a conditional variable, two other elements are needed:
a condition (typically implemented by checking a flag or a counter)
a mutex that protects the condition
The protocol then becomes,
acquire mutex
check condition
block and release mutex if condition is true, else release mutex
Semaphore is essentially a counter + a mutex + a wait queue. And it can be used as it is without external dependencies. You can use it either as a mutex or as a conditional variable.
Therefore, semaphore can be treated as a more sophisticated structure than conditional variable, while the latter is more lightweight and flexible.
Semaphores can be used to implement exclusive access to variables, however they are meant to be used for synchronization. Mutexes, on the other hand, have a semantics which is strictly related to mutual exclusion: only the process which locked the resource is allowed to unlock it.
Unfortunately you cannot implement synchronization with mutexes, that's why we have condition variables. Also notice that with condition variables you can unlock all the waiting threads in the same instant by using the broadcast unlocking. This cannot be done with semaphores.
semaphore and condition variables are very similar and are used mostly for the same purposes. However, there are minor differences that could make one preferable. For example, to implement barrier synchronization you would not be able to use a semaphore.But a condition variable is ideal.
Barrier synchronization is when you want all of your threads to wait until everyone has arrived at a certain part in the thread function. this can be implemented by having a static variable which is initially the value of total threads decremented by each thread when it reaches that barrier. this would mean we want each thread to sleep until the last one arrives.A semaphore would do the exact opposite! with a semaphore, each thread would keep running and the last thread (which will set semaphore value to 0) will go to sleep.
a condition variable on the other hand, is ideal. when each thread gets to the barrier we check if our static counter is zero. if not, we set the thread to sleep with the condition variable wait function. when the last thread arrives at the barrier, the counter value will be decremented to zero and this last thread will call the condition variable signal function which will wake up all the other threads!
I file condition variables under monitor synchronization. I've generally seen semaphores and monitors as two different synchronization styles. There are differences between the two in terms of how much state data is inherently kept and how you want to model code - but there really isn't any problem that can be solved by one but not the other.
I tend to code towards monitor form; in most languages I work in that comes down to mutexes, condition variables, and some backing state variables. But semaphores would do the job too.
semaphore need to know the count upfront for initialization. There is no such requirement for condition variables.
The the mutex and conditional variables are inherited from semaphore.
For mutex, the semaphore uses two states: 0, 1
For condition variables the semaphore uses counter.
They are like syntactic sugar
conditionalVar + mutex == semaphore

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