I've always been told to puts locks around variables that multiple threads will access, I've always assumed that this was because you want to make sure that the value you are working with doesn't change before you write it back
i.e.
mutex.lock()
int a = sharedVar
a = someComplexOperation(a)
sharedVar = a
mutex.unlock()
And that makes sense that you would lock that. But in other cases I don't understand why I can't get away with not using Mutexes.
Thread A:
sharedVar = someFunction()
Thread B:
localVar = sharedVar
What could possibly go wrong in this instance? Especially if I don't care that Thread B reads any particular value that Thread A assigns.
It depends a lot on the type of sharedVar, the language you're using, any framework, and the platform. In many cases, it's possible that assigning a single value to sharedVar may take more than one instruction, in which case you may read a "half-set" copy of the value.
Even when that's not the case, and the assignment is atomic, you may not see the latest value without a memory barrier in place.
MSDN Magazine has a good explanation of different problems you may encounter in multithreaded code:
Forgotten Synchronization
Incorrect Granularity
Read and Write Tearing
Lock-Free Reordering
Lock Convoys
Two-Step Dance
Priority Inversion
The code in your question is particularly vulnerable to Read/Write Tearing. But your code, having neither locks nor memory barriers, is also subject to Lock-Free Reordering (which may include speculative writes in which thread B reads a value that thread A never stored) in which side-effects become visible to a second thread in a different order from how they appeared in your source code.
It goes on to describe some known design patterns which avoid these problems:
Immutability
Purity
Isolation
The article is available here
The main problem is that the assignment operator (operator= in C++) is not always guaranteed to be atomic (not even for primitive, built in types). In plain English, that means that assignment can take more than a single clock cycle to complete. If, in the middle of that, the thread gets interrupted, then the current value of the variable might be corrupted.
Let me build off of your example:
Lets say sharedVar is some object with operator= defined as this:
object& operator=(const object& other) {
ready = false;
doStuff(other);
if (other.value == true) {
value = true;
doOtherStuff();
} else {
value = false;
}
ready = true;
return *this;
}
If thread A from your example is interrupted in the middle of this function, ready will still be false when thread B starts to run. This could mean that the object is only partially copied over, or is in some intermediate, invalid state when thread B attempts to copy it into a local variable.
For a particularly nasty example of this, think of a data structure with a removed node being deleted, then interrupted before it could be set to NULL.
(For some more information regarding structures that don't need a lock (aka, are atomic), here is another question that talks a bit more about that.)
This could go wrong, because threads can be suspended and resumed by the thread scheduler, so you can't be sure about the order these instructions are executed. It might just as well be in this order:
Thread B:
localVar = sharedVar
Thread A:
sharedVar = someFunction()
In which case localvar will be null or 0 (or some completeley unexpected value in an unsafe language), probably not what you intended.
Mutexes actually won't fix this particular issue by the way. The example you supply does not lend itself well for parallelization.
Related
The following implementation from Wikipedia:
volatile unsigned int produceCount = 0, consumeCount = 0;
TokenType buffer[BUFFER_SIZE];
void producer(void) {
while (1) {
while (produceCount - consumeCount == BUFFER_SIZE)
sched_yield(); // buffer is full
buffer[produceCount % BUFFER_SIZE] = produceToken();
// a memory_barrier should go here, see the explanation above
++produceCount;
}
}
void consumer(void) {
while (1) {
while (produceCount - consumeCount == 0)
sched_yield(); // buffer is empty
consumeToken(buffer[consumeCount % BUFFER_SIZE]);
// a memory_barrier should go here, the explanation above still applies
++consumeCount;
}
}
says that a memory barrier must be used between the line that accesses the buffer and the line that updates the Count variable.
This is done to prevent the CPU from reordering the instructions above the fence along-with that below it. The Count variable shouldn't be incremented before it is used to index into the buffer.
If a fence is not used, won't this kind of reordering violate the correctness of code? The CPU shouldn't perform increment of Count before it is used to index into buffer. Does the CPU not take care of data dependency while instruction reordering?
Thanks
If a fence is not used, won't this kind of reordering violate the correctness of code? The CPU shouldn't perform increment of Count before it is used to index into buffer. Does the CPU not take care of data dependency while instruction reordering?
Good question.
In c++, unless some form of memory barrier is used (atomic, mutex, etc), the compiler assumes that the code is single-threaded. In which case, the as-if rule says that the compiler may emit whatever code it likes, provided that the overall observable effect is 'as if' your code was executed sequentially.
As mentioned in the comments, volatile does not necessarily alter this, being merely an implementation-defined hint that the variable may change between accesses (this is not the same as being modified by another thread).
So if you write multi-threaded code without memory barriers, you get no guarantees that changes to a variable in one thread will even be observed by another thread, because as far as the compiler is concerned that other thread should not be touching the same memory, ever.
What you will actually observe is undefined behaviour.
It seems, that your question is "can incrementing Count and assigment to buffer be reordered without changing code behavior?".
Consider following code tansformation:
int count1 = produceCount++;
buffer[count1 % BUFFER_SIZE] = produceToken();
Notice that code behaves exactly as original one: one read from volatile variable, one write to volatile, read happens before write, state of program is the same. However, other threads will see different picture regarding order of produceCount increment and buffer modifications.
Both compiler and CPU can do that transformation without memory fences, so you need to force those two operations to be in correct order.
If a fence is not used, won't this kind of reordering violate the correctness of code?
Nope. Can you construct any portable code that can tell the difference?
The CPU shouldn't perform increment of Count before it is used to index into buffer. Does the CPU not take care of data dependency while instruction reordering?
Why shouldn't it? What would the payoff be for the costs incurred? Things like write combining and speculative fetching are huge optimizations and disabling them is a non-starter.
If you're thinking that volatile alone should do it, that's simply not true. The volatile keyword has no defined thread synchronization semantics in C or C++. It might happen to work on some platforms and it might happen not to work on others. In Java, volatile does have defined thread synchronization semantics, but they don't include providing ordering for accesses to non-volatiles.
However, memory barriers do have well-defined thread synchronization semantics. We need to make sure that no thread can see that data is available before it sees that data. And we need to make sure that a thread that marks data as able to be overwritten is not seen before the thread is finished with that data.
I'm having trouble figuring out a key point in wait-free algorithm design. Suppose a data structure has a pointer to another data structure (e.g. linked list, tree, etc), how can the right time for releasing a data structure?
The problem is this, there are separate operations that can't be executed atomically without a lock. For example one thread reads the pointer to some memory, and increments the use count for that memory to prevent free while this thread is using the data, which might take long, and even if it doesn't, it's a race condition. What prevents another thread from reading the pointer, decrementing the use count and determining that it's no longer used and freeing it before the first thread incremented the use count?
The main issue is that current CPUs only have a single word CAS (compare & swap). Alternatively the problem is that I'm clueless about waitfree algorithms and data structures and after reading some papers I'm still not seeing the light.
IMHO Garbage collection can't be the answer, because it would either GC would have to be prevented from running if any single thread is inside an atomic block (which would mean it can't be guaranteed that the GC will ever run again) or the problem is simply pushed to the GC, in which case, please explain how the GC would figure out if the data is in the silly state (a pointer is read [e.g. stored in a local variable] but the the use count didn't increment yet).
PS, references to advanced tutorials on wait-free algorithms for morons are welcome.
Edit: You should assume that the problem is being solved in a non-managed language, like C or C++. After all if it were Java, we'd have no need to worry about releasing memory. Further assume that the compiler may generate code that will store temporary references to objects in registers (invisible to other threads) right before the usage counter increment, and that a thread can be interrupted between loading the object address and incrementing the counter. This of course doesn't mean that the solution must be limited to C or C++, rather that the solution should give a set of primitives that allowing the implementation of wait-free algorithms on linked data structures. I'm interested in the primitives and how they solve the problem of designing wait-free algorithms. With such primitives a wait-free algorithm can be implemented equally well in C++ and Java.
After some research I learned this.
The problem is not trivial to solve and there are several solutions each with advantages and disadvantages. The reason for the complexity comes from inter CPU synchronization issues. If not done right it might appear to work correctly 99.9% of the time, which isn't enough, or it might fail under load.
Three solutions that I found are 1) hazard pointers, 2) quiescence period based reclamation (used by the Linux kernel in the RCU implementation) 3) reference counting techniques. 4) Other 5) Combinations
Hazard pointers work by saving the currently active references in a well-known per thread location, so any thread deciding to free memory (when the counter appears to be zero) can check if the memory is still in use by anyone. An interesting improvement is to buffer request to release memory in a small array and free them up in a batch when the array is full. The advantage of using hazard pointers is that it can actually guarantee an upper bound on unreclaimed memory. The disadvantage is that it places extra burden on the reader.
Quiescence period based reclamation works by delaying the actual release of the memory until it's known that each thread has had a chance to finish working on any data that may need to be released. The way to know that this condition is satisfied is to check if each thread passed through a quiescent period (not in a critical section) after the object was removed. In the Linux kernel this means something like each task making a voluntary task switch. In a user space application it would be the end of a critical section. This can be achieved by a simple counter, each time the counter is even the thread is not in a critical section (reading shared data), each time the counter is odd the thread is inside a critical section, to move from a critical section or back all the thread needs to do is to atomically increment the number. Based on this the "garbage collector" can determine if each thread has had a chance to finish. There are several approaches, one simple one would be to queue up the requests to free memory (e.g. in a linked list or an array), each with the current generation (managed by the GC), when the GC runs it checks the state of the threads (their state counters) to see if each passed to the next generation (their counter is higher than the last time or is the same and even), any memory can be reclaimed one generation after it was freed. The advantage of this approach is that is places the least burden on the reading threads. The disadvantage is that it can't guarantee an upper bound for the memory waiting to be released (e.g. one thread spending 5 minutes in a critical section, while the data keeps changing and memory isn't released), but in practice it works out all right.
There is a number of reference counting solutions, many of them require double compare and swap, which some CPUs don't support, so can't be relied upon. The key problem remains though, taking a reference before updating the counter. I didn't find enough information to explain how this can be done simply and reliably though. So .....
There are of course a number of "Other" solutions, it's a very important topic of research with tons of papers out there. I didn't examine all of them. I only need one.
And of course the various approaches can be combined, for example hazard pointers can solve the problems of reference counting. But there's a nearly infinite number of combinations, and in some cases a spin lock might theoretically break wait-freedom, but doesn't hurt performance in practice. Somewhat like another tidbit I found in my research, it's theoretically not possible to implement wait-free algorithms using compare-and-swap, that's because in theory (purely in theory) a CAS based update might keep failing for non-deterministic excessive times (imagine a million threads on a million cores each trying to increment and decrement the same counter using CAS). In reality however it rarely fails more than a few times (I suspect it's because the CPUs spend more clocks away from CAS than there are CPUs, but I think if the algorithm returned to the same CAS on the same location every 50 clocks and there were 64 cores there could be a chance of a major problem, then again, who knows, I don't have a hundred core machine to try this). Another results of my research is that designing and implementing wait-free algorithms and data-structures is VERY challenging (even if some of the heavy lifting is outsourced, e.g. to a garbage collector [e.g. Java]), and might perform less well than a similar algorithm with carefully placed locks.
So, yeah, it's possible to free memory even without delays. It's just tricky. And if you forget to make the right operations atomic, or to place the right memory barrier, oh, well, you're toast. :-) Thanks everyone for participating.
I think atomic operations for increment/decrement and compare-and-swap would solve this problem.
Idea:
All resources have a counter which is modified with atomic operations. The counter is initially zero.
Before using a resource: "Acquire" it by atomically incrementing its counter. The resource can be used if and only if the incremented value is greater than zero.
After using a resource: "Release" it by atomically decrementing its counter. The resource should be disposed/freed if and only if the decremented value is equal to zero.
Before disposing: Atomically compare-and-swap the counter value with the minimum (negative) value. Dispose will not happen if a concurrent thread "Acquired" the resource in between.
You haven't specified a language for your question. Here goes an example in c#:
class MyResource
{
// Counter is initially zero. Resource will not be disposed until it has
// been acquired and released.
private int _counter;
public bool Acquire()
{
// Atomically increment counter.
int c = Interlocked.Increment(ref _counter);
// Resource is available if the resulting value is greater than zero.
return c > 0;
}
public bool Release()
{
// Atomically decrement counter.
int c = Interlocked.Decrement(ref _counter);
// We should never reach a negative value
Debug.Assert(c >= 0, "Resource was released without being acquired");
// Dispose when we reach zero
if (c == 0)
{
// Mark as disposed by setting counter its minimum value.
// Only do this if the counter remain at zero. Atomic compare-and-swap operation.
if (Interlocked.CompareExchange(ref _counter, int.MinValue, c) == c)
{
// TODO: Run dispose code (free stuff)
return true; // tell caller that resource is disposed
}
}
return false; // released but still in use
}
}
Usage:
// "r" is an instance of MyResource
bool acquired = false;
try
{
if (acquired = r.Acquire())
{
// TODO: Use resource
}
}
finally
{
if (acquired)
{
if (r.Release())
{
// Resource was disposed.
// TODO: Nullify variable or similar to let GC collect it.
}
}
}
I know this is not the best way but it works for me:
for shared dynamic data-structure lists I use usage counter per item
for example:
struct _data
{
DWORD usage;
bool delete;
// here add your data
_data() { usage=0; deleted=true; }
};
const int MAX = 1024;
_data data[MAX];
now when item is started to be used somwhere then
// start use of data[i]
data[i].cnt++;
after is no longer used then
// stop use of data[i]
data[i].cnt--;
if you want to add new item to list then
// add item
for (i=0;i<MAX;i++) // find first deleted item
if (data[i].deleted)
{
data[i].deleted=false;
data[i].cnt=0;
// copy/set your data
break;
}
and now in the background once in a while (on timer or whatever)
scann data[] an all undeleted items with cnt == 0 set as deleted (+ free its dynamic memory if it has any)
[Note]
to avoid multi-thread access problems implement single global lock per data list
and program it so you cannot scann data while any data[i].cnt is changing
one bool and one DWORD suffice for this if you do not want to use OS locks
// globals
bool data_cnt_locked=false;
DWORD data_cnt=0;
now any change of data[i].cnt modify like this:
// start use of data[i]
while (data_cnt_locked) Sleep(1);
data_cnt++;
data[i].cnt++;
data_cnt--;
and modify delete scan like this
while (data_cnt) Sleep(1);
data_cnt_locked=true;
Sleep(1);
if (data_cnt==0) // just to be sure
for (i=0;i<MAX;i++) // here scan for items to delete ...
if (!data[i].cnt)
if (!data[i].deleted)
{
data[i].deleted=true;
data[i].cnt=0;
// release your dynamic data ...
}
data_cnt_locked=false;
PS.
do not forget to play with the sleep times a little to suite your needs
lock free algorithm sleep times are sometimes dependent on OS task/scheduler
this is not really an lock free implementation
because while GC is at work then all is locked
but if ather than that multi access is not blocking to each other
so if you do not run GC too often you are fine
Let's say I'm programming in a threading framework that does not have multiple-reader/single-writer mutexes. Can I implement their functionality with the following:
Create two mutexes: a recursive (lock counting) one for readers and a binary one for the writer.
Write:
acquire lock on binary mutex
wait until recursive mutex has lock count zero
actual write
release lock on binary mutex
Read:
acquire lock on binary mutex (so I know the writer is not active)
increment count of recursive mutex
release lock on binary mutex
actual read
decrement count of recursive mutex
This is not homework. I have no formal training in concurrent programming, and am trying to grasp the issues. If someone can point out a flaw, spell out the invariants or provide a better algorithm, I'd be very pleased. A good reference, either online or on dead trees, would also be appreciated.
The following is taken directly from The Art of Multiprocessor Programming which is a good book to learn about this stuff. There's actually 2 implementations presented: a simple version and a fair version. I'll go ahead and reproduce the fair version.
One of the requirements for this implementation is that you have a condition variable primitive. I'll try to figure out a way to remove it but that might take me a little while. Until then, this should still be better than nothing. Note that it's also possible to implement this primitive using only locks.
public class FifoReadWriteLock {
int readAcquires = 0, readReleases = 0;
boolean writer = false;
ReentrantLock lock;
Condition condition = lock.newCondition(); // This is the condition variable.
void readLock () {
lock.lock();
try {
while(writer)
condition.await();
readAcquires++;
}
finally {
lock.unlock();
}
}
void readUnlock () {
lock.lock();
try {
readReleases++;
if (readAcquires == readReleases)
condition.signalAll();
}
finally {
lock.unlock();
}
}
void writeLock () {
lock.lock();
try {
while (writer)
condition.await();
writer = true;
while (readAcquires != readReleases)
condition.await();
}
finally {
lock.unlock();
}
}
void writeUnlock() {
writer = false;
condition.signalAll();
}
}
First off, I simplified the code a little but the algorithm remains the same. There also happens to be an error in the book for this algorithm which is corrected in the errata. If you plan on reading the book, keep the errata close by or you'll end up being very confused (like me a few minutes ago when I was trying to re-understand the algorithm). Note that on the bright side, this is a good thing since it keeps you on your toes and that's a requirement when you're dealing with concurrency.
Next, while this may be a Java implementation, only use it as pseudo code. When doing the actual implementation you'll have to be carefull about the memory model of the language or you'll definitely end up with a headache. As an example, I think that the readAcquires and readReleases and writer variable all have to be declared as volatile in Java or the compiler is free to optimize them out of the loops. This is because in a strictly sequential programs there's no point in continuously looping on a variable that is never changed inside the loop. Note that my Java is a little rusty so I might be wrong. There's also another issue with integer overflow of the readReleases and readAcquires variables which is ignored in the algorithm.
One last note before I explain the algorithm. The condition variable is initialized using the lock. That means that when a thread calls condition.await(), it gives up its ownership of the lock. Once it's woken up by a call to condition.signalAll() the thread will resume once it has reacquired the lock.
Finally, here's how and why it works. The readReleases and readAcquires variables keep track of the number threads that have acquired and released the read lock. When these are equal, no thread has the read lock. The writer variable indicates that a thread is trying to acquire the write lock or it already has it.
The read lock part of the algorithm is fairly simple. When trying to lock, it first checks to see if a writer is holding the lock or is trying to acquire it. If so, it waits until the writer is done and then claims the lock for the readers by incrementing the readAcquires variable. When unlocking, a thread increases the readReleases variable and if there's no more readers, it notifies any writers that may be waiting.
The write lock part of the algorithm isn't much more complicated. To lock, a thread must first check whether any other writer is active. If they are, it has to wait until the other writer is done. It then indicates that it wants the lock by setting writer to true (note that it doesn't hold it yet). It then waits until there's no more readers before continuing. To unlock, it simply sets the variable writer to false and notifies any other threads that might be waiting.
This algorithm is fair because the readers can't block a writer indefinitely. Once a writer indicates that it wants to acquire the lock, no more readers can acquire the lock. After that the writer simply waits for the last remaining readers to finish up before continuing. Note that there's still the possibility of a writer indefinitely blocking another writer. That's a fairly rare case but the algorithm could be improved to take that into account.
So I re-read your question and realised that I partly (badly) answered it with the algorithm presented below. So here's my second attempt.
The algorithm, you described is fairly similar to the simple version presented in the book I mentionned. The only problem is that A) it's not fair and B) I'm not sure how you would implement wait until recursive mutex has lock count zero. For A), see above and for B), the book uses a single int to keep track of the readers and a condition variable to do the signalling.
You may want to prevent write starvation, to accomplish this you can either give preference to writes or make mutex fair.
ReadWriteLock Java's interface documentation says Writer preference is common,
ReentrantReadWriteLock class documentation says
This class does not impose a reader or writer preference ordering for lock access. However, it does support an optional fairness policy.
Note R..'s comment
Rather than locking and unlocking the binary mutex for reading, you
can just check the binary mutex state after incrementing the count on
the recursive mutex, and wait (spin/yield/futex_wait/whatever) if it's
locked until it becomes unlocked
Recommended reading:
Programming with POSIX Threads
Perl's RWLock
Java's ReadWriteLock documentation.
I have this POSIX thread:
void subthread(void)
{
while(!quit_thread) {
// do something
...
// don't waste cpu cycles
if(!quit_thread) usleep(500);
}
// free resources
...
// tell main thread we're done
quit_thread = FALSE;
}
Now I want to terminate subthread() from my main thread. I've tried the following:
quit_thread = TRUE;
// wait until subthread() has cleaned its resources
while(quit_thread);
But it does not work! The while() clause does never exit although my subthread clearly sets quit_thread to FALSE after having freed its resources!
If I modify my shutdown code like this:
quit_thread = TRUE;
// wait until subthread() has cleaned its resources
while(quit_thread) usleep(10);
Then everything is working fine! Could someone explain to me why the first solution does not work and why the version with usleep(10) suddenly works? I know that this is not a pretty solution. I could use semaphores/signals for this but I'd like to learn something about multithreading, so I'd like to know why my first solution doesn't work.
Thanks!
Without a memory fence, there is no guarantee that values written in one thread will appear in another. Most of the pthread primitives introduce a barrier, as do several system calls such as usleep. Using a mutex around both the read and write introduces a barrier, and more generally prevents multi-byte values being visible in partially written state.
You also need to separate the idea of asking a thread to stop executing, and reporting that it has stopped, and appear to be using the same variable for both.
What's most likely to be happening is that your compiler is not aware that quit_thread can be changed by another thread (because C doesn't know about threads, at least at the time this question was asked). Because of that, it's optimising the while loop to an infinite loop.
In other words, it looks at this code:
quit_thread = TRUE;
while(quit_thread);
and thinks to itself, "Hah, nothing in that loop can ever change quit_thread to FALSE, so the coder obviously just meant to write while (TRUE);".
When you add the call to usleep, the compiler has another think about it and assumes that the function call may change the global, so it plays it safe and doesn't optimise it.
Normally you would mark the variable as volatile to stop the compiler from optimising it but, in this case, you should use the facilities provided by pthreads and join to the thread after setting the flag to true (and don't have the sub-thread reset it, do that in the main thread after the join if it's necessary). The reason for that is that a join is likely to be more efficient than a continuous loop waiting for a variable change since the thread doing the join will most likely not be executed until the join needs to be done.
In your spinning solution, the joining thread will most likely continue to run and suck up CPU grunt.
In other words, do something like:
Main thread Child thread
------------------- -------------------
fStop = false
start Child Initialise
Do some other stuff while not fStop:
fStop = true Do what you have to do
Finish up and exit
join to Child
Do yet more stuff
And, as an aside, you should technically protect shared variables with mutexes but this is one of the few cases where it's okay, one-way communication where half-changed values of a variable don't matter (false/not-false).
The reason you normally mutex-protect a variable is to stop one thread seeing it in a half-changed state. Let's say you have a two-byte integer for a count of some objects, and it's set to 0x00ff (255).
Let's further say that thread A tries to increment that count but it's not an atomic operation. It changes the top byte to 0x01 but, before it gets a chance to change the bottom byte to 0x00, thread B swoops in and reads it as 0x01ff.
Now that's not going to be very good if thread B want to do something with the last element counted by that value. It should be looking at 0x0100 but will instead try to look at 0x01ff, the effect of which will be wrong, if not catastrophic.
If the count variable were protected by a mutex, thread B wouldn't be looking at it until thread A had finished updating it, hence no problem would occur.
The reason that doesn't matter with one-way booleans is because any half state will also be considered as true or false so, if thread A was halfway between turning 0x0000 into 0x0001 (just the top byte), thread B would still see that as 0x0000 (false) and keep going (until thread A finishes its update next time around).
And if thread A was turning the boolean into 0xffff, the half state of 0xff00 would still be considered true by thread B so it would do its thing before thread A had finished updating the boolean.
Neither of those two possibilities is bad simply because, in both, thread A is in the process of changing the boolean and it will finish eventually. Whether thread B detects it a tiny bit earlier or a tiny bit later doesn't really matter.
The while(quite_thread); is using the value quit_thread was set to on the line before it. Calling a function (usleep) induces the compiler to reload the value on each test.
In any case, this is the wrong way to wait for a thread to complete. Use pthread_join instead.
You're "learning" multhithreading the wrong way. The right way is to learn to use mutexes and condition variables; any other solution will fail under some circumstances.
I understand about race conditions and how with multiple threads accessing the same variable, updates made by one can be ignored and overwritten by others, but what if each thread is writing the same value (not different values) to the same variable; can even this cause problems? Could this code:
GlobalVar.property = 11;
(assuming that property will never be assigned anything other than 11), cause problems if multiple threads execute it at the same time?
The problem comes when you read that state back, and do something about it. Writing is a red herring - it is true that as long as this is a single word most environments guarantee the write will be atomic, but that doesn't mean that a larger piece of code that includes this fragment is thread-safe. Firstly, presumably your global variable contained a different value to begin with - otherwise if you know it's always the same, why is it a variable? Second, presumably you eventually read this value back again?
The issue is that presumably, you are writing to this bit of shared state for a reason - to signal that something has occurred? This is where it falls down: when you have no locking constructs, there is no implied order of memory accesses at all. It's hard to point to what's wrong here because your example doesn't actually contain the use of the variable, so here's a trivialish example in neutral C-like syntax:
int x = 0, y = 0;
//thread A does:
x = 1;
y = 2;
if (y == 2)
print(x);
//thread B does, at the same time:
if (y == 2)
print(x);
Thread A will always print 1, but it's completely valid for thread B to print 0. The order of operations in thread A is only required to be observable from code executing in thread A - thread B is allowed to see any combination of the state. The writes to x and y may not actually happen in order.
This can happen even on single-processor systems, where most people do not expect this kind of reordering - your compiler may reorder it for you. On SMP even if the compiler doesn't reorder things, the memory writes may be reordered between the caches of the separate processors.
If that doesn't seem to answer it for you, include more detail of your example in the question. Without the use of the variable it's impossible to definitively say whether such a usage is safe or not.
It depends on the work actually done by that statement. There can still be some cases where Something Bad happens - for example, if a C++ class has overloaded the = operator, and does anything nontrivial within that statement.
I have accidentally written code that did something like this with POD types (builtin primitive types), and it worked fine -- however, it's definitely not good practice, and I'm not confident that it's dependable.
Why not just lock the memory around this variable when you use it? In fact, if you somehow "know" this is the only write statement that can occur at some point in your code, why not just use the value 11 directly, instead of writing it to a shared variable?
(edit: I guess it's better to use a constant name instead of the magic number 11 directly in the code, btw.)
If you're using this to figure out when at least one thread has reached this statement, you could use a semaphore that starts at 1, and is decremented by the first thread that hits it.
I would expect the result to be undetermined. As in it would vary from compiler to complier, langauge to language and OS to OS etc. So no, it is not safe
WHy would you want to do this though - adding in a line to obtain a mutex lock is only one or two lines of code (in most languages), and would remove any possibility of problem. If this is going to be two expensive then you need to find an alternate way of solving the problem
In General, this is not considered a safe thing to do unless your system provides for atomic operation (operations that are guaranteed to be executed in a single cycle).
The reason is that while the "C" statement looks simple, often there are a number of underlying assembly operations taking place.
Depending on your OS, there are a few things you could do:
Take a mutual exclusion semaphore (mutex) to protect access
in some OS, you can temporarily disable preemption, which guarantees your thread will not swap out.
Some OS provide a writer or reader semaphore which is more performant than a plain old mutex.
Here's my take on the question.
You have two or more threads running that write to a variable...like a status flag or something, where you only want to know if one or more of them was true. Then in another part of the code (after the threads complete) you want to check and see if at least on thread set that status... for example
bool flag = false
threadContainer tc
threadInputs inputs
check(input)
{
...do stuff to input
if(success)
flag = true
}
start multiple threads
foreach(i in inputs)
t = startthread(check, i)
tc.add(t) // Keep track of all the threads started
foreach(t in tc)
t.join( ) // Wait until each thread is done
if(flag)
print "One of the threads were successful"
else
print "None of the threads were successful"
I believe the above code would be OK, assuming you're fine with not knowing which thread set the status to true, and you can wait for all the multi-threaded stuff to finish before reading that flag. I could be wrong though.
If the operation is atomic, you should be able to get by just fine. But I wouldn't do that in practice. It is better just to acquire a lock on the object and write the value.
Assuming that property will never be assigned anything other than 11, then I don't see a reason for assigment in the first place. Just make it a constant then.
Assigment only makes sense when you intend to change the value unless the act of assigment itself has other side effects - like volatile writes have memory visibility side-effects in Java. And if you change state shared between multiple threads, then you need to synchronize or otherwise "handle" the problem of concurrency.
When you assign a value, without proper synchronization, to some state shared between multiple threads, then there's no guarantees for when the other threads will see that change. And no visibility guarantees means that it it possible that the other threads will never see the assignt.
Compilers, JITs, CPU caches. They're all trying to make your code run as fast as possible, and if you don't make any explicit requirements for memory visibility, then they will take advantage of that. If not on your machine, then somebody elses.