I've learnt that semaphore can act as an atomic lock that can perform two function: down and up.
Is there any way, to swap the value of two pointers atomically, avoiding race condition and deadlock.
I first came up with the 'solution', suppose both pointers has :
Item a = { value = "A", lock = Semaphore(1) }
Item b = { value = "B", lock = Semaphore(1) }
void atomic_swap(Item* a, Item* b) {
a->lock.down(); // acquire
b->lock.down(); // acquire
non_atomic_swap(&a.value, &b.value);
b->lock.up(); // release
a->lock.up(); // release
}
But if I am not wrong, it will result to deadlock if two atomic_swap is called using same pointers: eg.
Item a = ...;
Item b = ...;
thread_start(atomic_swap, {&a, &b}); // start a thread running atomic_swap(&a, &b);
thread_start(atomic_swap, {&b, &a}); // start a thread running atomic_swap(&b, &a);
On the code above, if both call to atomic_swap arrive the first down simultaneously, the next down will block forever, which results to deadlock.
One of the solution I can think about to avoid deadlock is assign a 'group' to them, only item in the same group can perform atomic_swap safely (without deadlock):
Group g = { lock = Semaphore(1) };
Item a = { value = "A", group = g };
Item b = { value = "B", group = g };
void atomic_swap(Item* a, Item* b) {
// assume a->group == b->group
a->group.down() // b->group.down()
non_atomic_swap(&a.value, &b.value);
a->group.up(); // b->group.up();
}
But this of course require every item to carry a group, and unrelated items might wait for the group because of other calls.
Is there any good way to perform the atomic_swap theoretically using semaphore?
You can use std::less to compare the pointers to ensure that all users acquire the locks in the same order:
void atomic_swap(Item* a, Item* b) {
std::less<Item *> cmp;
if (cmp(a, b)) {
a->lock.down();
b->lock.down();
} else {
b->lock.down();
a->lock.down(); }
non_atomic_swap(&a->value, &b->value);
b->lock.up(); // release
a->lock.up(); // release
}
Related
https://github.com/gameprogcpp/code/blob/master/Chapter02/Game.cpp
std::vector<Actor*> deadActors;
for (auto actor : mActors)
{
if (actor->GetState() == Actor::EDead)
{
deadActors.emplace_back(actor);
}
}
// Delete dead actors (which removes them from mActors)
for (auto actor : deadActors)
{
delete actor;
}
how is it okay?
when pointers in deadActors are deleted, their is no memory loss in mActors?
// Delete dead actors (which removes them from mActors)
This is incorrect; deleting the Actors does not modify the original vector. It only results in dereferencing the pointers to those Actors to be undefined behaviour.
You'd need an additional step removing the pointers from the original vector for this reason.
You could simply iterate through the vector removing the dead elements in one go though:
auto writePos = std::find_if(mActor.begin(), mActor.end(), [this](Actor* actor) {return actor->GetState() == Actor::EDead; });
if (writePos != mActor.end())
{
delete *writePos; // delete first
// move actors and delete dead ones
for (auto readPos = writePos + 1, end = mActor.end(); readPos != end; ++readPos)
{
if ((**readPos).GetState() == Actor::EDead)
{
delete *readPos;
}
else
{
// move non dead actor
*writePos = *readPos;
++writePos;
}
}
// remove unneeded space from the end
mActor.erase(writePos, mActor.end());
}
Note that this becomes much simpler, if you use an element type for the mActor vector that manages the lifetime of the Actor object. std::unique_ptr<Actor> would do the trick. This way any element erased from the vector automatically results in the deletion of the Actor object:
std::vector<std::unique_ptr<Actor>> actors = ...;
// remove all dead actors moving the remaining actors to the front
auto removeEnd = std::remove_if(actors.begin(), actors.end(), [](std::unique_ptr<Actor> const& actor) { return actor->GetState() == Actor::EDead; });
// remove extra space
std::actors.erase(removeEnd, actors.end());
Or with C++20:
std::vector<std::unique_ptr<Actor>> actors = ...;
std::erase_if(actors.begin(), actors.end(), [](std::unique_ptr<Actor> const& actor) { return actor->GetState() == Actor::EDead; });
I am using atomics and a circular buffer in order to implement a multi-reader threads, multi-writer threads object pool.
It is difficult to investigate because instrumenting code leads to bug vanishment !
The model
Producers (or writer threads) request an Element to the Ring in order to 'prepare' the element. When terminated, the writer thread changes the element state so a reader can 'consume' it. After that, the element becomes available again for writing.
Consumers (or reader threads) request an object to the Ring in order to 'read' the object.
After 'releasing' the object, the object is in a state::Ready state, eg available to be consume by a reader thread.
It can fail if no object is available eg the next free object in the Ring is not on state::Unused state.
The 2 classes, Element and Ring
Element :
to be written, a writer thread must successfully exchange the _state member from state::Unused to state::LockForWrite
when finished, the writer thread force the state to state::Ready (it should be the only to handle this Element)
to be read, a rader thread must successfully exchange the _state member from state::Ready to state::LockForRead
when finished, the reader thread force the state to state::Unused (it should be the only to handle this Element)
Summarized :
writers lifecycle : state::Unused -> state::LockForWrite -> state::Ready
readers lifecycle : state::Ready -> state::LockForRead -> state::Unused
Ring
has a vector of Element , seen as a circular buffer.
std::atomic<int64_t> _read, _write; are the 2 indexes used to access the elements via :
_elems[ _write % _elems.size() ] for writers,
_elems[ _read % _elems.size() ] for readers.
When a reader has successfully LockForRead an object, the _read index is incremented.
When a writer has successfully LockForWrite an object, the _write index is incremented.
The main :
We add to a vector some writers and readers threads sharing the same Ring. Each thread just try to get_read or get_write element and release them just after.
Based on Element transition everything should be fine but one can observe that the Ring at some point gets blocked like because some elements in the ring are in state state::Ready with a _write % _elems.size() index pointing on it and symetrically, some elements in the ring are in state state::Unused with a _read % _elems.size() index pointing on it ! Both = deadlock.
#include<atomic>
#include<vector>
#include<thread>
#include<iostream>
#include<cstdint>
typedef enum : int
{
Unused, LockForWrite, Ready, LockForRead
}state;
class Element
{
std::atomic<state> _state;
public:
Element():_state(Unused){ }
// a reader need to successfully make the transition Ready => LockForRead
bool lock_for_read() { state s = Ready; return _state.compare_exchange_strong(s, LockForRead); }
void unlock_read() { state s = Unused; _state.store(s); }
// a reader need to successfully make the transition Unused => LockForWrite
bool lock_for_write() { state s = Unused; return _state.compare_exchange_strong(s, LockForWrite); }
void unlock_write() { state s = Ready; _state.store(s); }
};
class Ring
{
std::vector<Element> _elems;
std::atomic<int64_t> _read, _write;
public:
Ring(size_t capacity)
: _elems(capacity), _read(0), _write(0) {}
Element * get_for_read() {
Element * ret = &_elems[ _read.load() % _elems.size() ];
if (!ret->lock_for_read()) // if success, the object belongs to the caller thread as reader
return NULL;
_read.fetch_add(1); // success! incr _read index
return ret;
}
Element * get_for_write() {
Element * ret = &_elems[ _write.load() % _elems.size() ];
if (!ret->lock_for_write())// if success, the object belongs to the caller thread as writer
return NULL;
_write.fetch_add(1); // success! incr _write index
return ret;
}
void release_read(Element* e) { e->unlock_read();}
void release_write(Element* e) { e->unlock_write();}
};
int main()
{
const int capacity = 10; // easy to process modulo[![enter image description here][1]][1]
std::atomic<bool> stop=false;
Ring ring(capacity);
std::function<void()> writer_job = [&]()
{
std::cout << "writer starting" << std::endl;
Element * e;
while (!stop)
{
if (!(e = ring.get_for_write()))
continue;
// do some real writer job ...
ring.release_write(e);
}
};
std::function<void()> reader_job = [&]()
{
std::cout << "reader starting" << std::endl;
Element * e;
while (!stop)
{
if (!(e = ring.get_for_read()))
continue;
// do some real reader job ...
ring.release_read(e);
}
};
int nb_writers = 1;
int nb_readers = 2;
std::vector<std::thread> threads;
threads.reserve(nb_writers + nb_readers);
std::cout << "adding writers" << std::endl;
while (nb_writers--)
threads.push_back(std::thread(writer_job));
std::cout << "adding readers" << std::endl;
while (nb_readers--)
threads.push_back(std::thread(reader_job));
// wait user key press, halt in debugger after 1 or 2 seconds
// in order to reproduce problem and watch ring
std::cin.get();
stop = true;
std::cout << "waiting all threads...\n";
for (auto & th : threads)
th.join();
std::cout << "end" << std::endl;
}
This "watch debugger screeshot" has been took pausing the program after running 1 second. As you can see, _read is pointing to the element 8 marked as state::Unused so no transition can unblock this state for this reader, except a writer but _write index is pointing on element 0 with state state::Ready !
My question: what did I missed in this ? Structurally I am sure the sequence is correct but I am missing some atomic trick ...
os tested : rhel5/gcc 4.1.2, rhel 7/gcc 4.8, win10/ms visual 2015, win10/mingw
Yann's answer is correct about the problem: your threads can create "holes" in the sequence by reading and writing elements out-of-order if there's a delay between the read/write lock and the increment of the index. The fix is to verify that the index has not changed between the initial read and the increment, a la:
class Element
{
std::atomic<state> _state;
public:
Element():_state(Unused){ }
// a reader need to successfully make the transition Ready => LockForRead
bool lock_for_read() {
state s = Ready;
return _state.compare_exchange_strong(s, LockForRead);
}
void abort_read() { _state = Ready; }
void unlock_read() { state s = Unused; _state.store(s); }
// a reader need to successfully make the transition Unused => LockForWrite
bool lock_for_write() {
state s = Unused;
return _state.compare_exchange_strong(s, LockForWrite);
}
void abort_write() { _state = Unused; }
void unlock_write() { state s = Ready; _state.store(s); }
};
class Ring
{
std::vector<Element> _elems;
std::atomic<int64_t> _read, _write;
public:
Ring(size_t capacity)
: _elems(capacity), _read(0), _write(0) {}
Element * get_for_read() {
auto i = _read.load();
Element * ret = &_elems[ i % _elems.size() ];
if (ret->lock_for_read()) {
// if success, the object belongs to the caller thread as reader
if (_read.compare_exchange_strong(i, i + 1))
return ret;
// Woops, reading out of order.
ret->abort_read();
}
return NULL;
}
Element * get_for_write() {
auto i = _write.load();
Element * ret = &_elems[ i % _elems.size() ];
if (ret->lock_for_write()) {
// if success, the object belongs to the caller thread as writer
if (_write.compare_exchange_strong(i, i + 1))
return ret;
// Woops, writing out of order.
ret->abort_write();
}
return NULL;
}
void release_read(Element* e) { e->unlock_read();}
void release_write(Element* e) { e->unlock_write();}
};
You do not have atomic section around the increment of the two shared counters _read and _write.
That looks bad to me, you could switch another element without meaning to.
Imagine this scenario,
1 reader R1 and 1 writer W are happily cooperating.
Reader 2 executes : Element * ret = &_elems[ _read.load() % _elems.size() ];
and gets pushed off the cpu.
Now R1 and W are still playing together, so the positions of _read and _write are now arbitrary w.r.t. the element ret that R2 is pointing.
Now at some point R2 gets scheduled, and it so happens that *ret_ is readable (again possibly, R1 and W went around the block a few times).
Ouch, as you see, we will read it, and increment "_read", but _read has no relation to _ret. This creates kind of holes, elements that have not been read, but that are below _read index.
So, make critical sections to ensure that increment of _read/_write is done in the same semantic step as the actual lock.
First, how D create parallel foreach (underlying logic)?
int main(string[] args)
{
int[] arr;
arr.length = 100000000;
/* Why it is working?, it's simple foreach which working with
reference to int from arr, parallel function return ParallelForeach!R
(ParallelForeach!int[]), but I don't know what it is.
Parallel function is part od phobos library, not D builtin function, then what
kind of magic is used for this? */
foreach (ref e;parallel(arr))
{
e = 100;
}
foreach (ref e;parallel(arr))
{
e *= e;
}
return 0;
}
And second, why it is slower then simple foreach?
Finally, If I create my own taskPool (and don't use global taskPool object), program never end. Why?
parallel returns a struct (of type ParallelForeach) that implements the opApply(int delegate(...)) foreach overload.
when called the struct submits a parallel function to the private submitAndExecute which submits the same task to all threads in the pool.
this then does:
scope(failure)
{
// If an exception is thrown, all threads should bail.
atomicStore(shouldContinue, false);
}
while (atomicLoad(shouldContinue))
{
immutable myUnitIndex = atomicOp!"+="(workUnitIndex, 1);
immutable start = workUnitSize * myUnitIndex;
if(start >= len)
{
atomicStore(shouldContinue, false);
break;
}
immutable end = min(len, start + workUnitSize);
foreach(i; start..end)
{
static if(withIndex)
{
if(dg(i, range[i])) foreachErr();
}
else
{
if(dg(range[i])) foreachErr();
}
}
}
where workUnitIndex and shouldContinue are shared variables and dg is the foreach delegate
The reason it is slower is simply because of the overhead required to pass the function to the threads in the pool and atomically accessing the shared variables.
the reason your custom pool doesn't shut down is likely you don't shut down the threadpool with finish
I have a while (!Queue.empty()) loop that processes a queue of elements. There are a series of pattern matchers going from highest-priority to lowest-priority order. When a pattern is matched, the corresponding element is removed from the queue, and matching is restarted from the top (so that the highest-priority matchers get a chance to act first).
So right now it looks something like this (a simplified version):
while (!Queue.empty())
{
auto & Element = *Queue.begin();
if (MatchesPatternA(Element)) { // Highest priority, since it's first
// Act on it
// Remove Element from queue
continue;
}
if (MatchesPatternB(Element)) {
// Act on it
// Remove Element from queue
continue;
}
if (MatchesPatternC(Element)) { // Lowest priority, since it's last
// Act on it
// Remove Element from queue
continue;
}
// If we got this far, that means no pattern was matched, so
// Remove Element from queue
}
This works, but I want to refactor this loop in some way to remove the use of the keyword continue.
Why? Because if I want to outsource a pattern matching to an external function, it obviously breaks. E.g.
void ExternalMatching(...)
{
if (MatchesPatternB(Element)) {
// Act on it
// Remove Element from queue
continue; // This won't work here
}
}
while (!Queue.empty())
{
auto & Element = *Queue.begin();
if (MatchesPatternA(Element)) {
// Act on it
// Remove Element from queue
continue;
}
ExternalMatching(...);
if (MatchesPatternC(Element)) {
// Act on it
// Remove Element from queue
continue;
}
// If we got this far, that means no pattern was matched, so
// Remove Element from queue
}
I don't want to have to write repetitive if statements like if (ExternalMatching(...)) { ... continue; }, I'd rather find a cleaner way to express this logic.
This simplified example might make it seem like a good idea to make pattern matching more general rather than having distinct MatchesPatternA, MatchesPatternB, MatchesPatternC, etc. functions. But in my situation the patterns are quite complicated, and I'm not quite ready to generalize them yet. So I want to keep that part as is, separate functions.
Any elegant ideas? Thank you!
If you have access to C++11 I would like to suggest another solution. Basicaly I created a container of handlers and actions that can be adjusted in runtime. It may be a pro or con for your design depending on your requirements. Here it is:
#include <functional>
typedef std::pair<std::function<bool(const ElementType &)>,
std::function<void(ElementType &)> > HandlerData;
typedef std::vector<HandlerData> HandlerList;
HandlerList get_handlers()
{
HandlerList handlers;
handlers.emplace_back([](const ElementType &el){ return MatchesPatternA(el); },
[](ElementType &el){ /* Action */ });
handlers.emplace_back([](const ElementType &el){ return MatchesPatternB(el); },
[](ElementType &el){ /* Action */ });
handlers.emplace_back([](const ElementType &el){ return MatchesPatternC(el); },
[](ElementType &el){ /* Action */ });
return handlers;
}
int main()
{
auto handlers = get_handlers();
while(!Queue.empty()) {
auto &Element = *Queue.begin();
for(auto &h : handlers) {
// check if handler matches the element
if(h.first(Element)) {
// act on element
h.second(Element);
break;
}
}
// remove element
Queue.pop_front();
}
}
I would recommend using a function that does the pattern matching (but does not act on the result) and then a set of functions that act on the different options:
enum EventType {
A, B, C //, D, ...
};
while (!queue.empty()) {
auto & event = queue.front();
EventType e = eventType(event); // Internally does MatchesPattern*
// and returns the match
switch (e) {
case A:
processA(event);
break;
case B:
processB(event);
This way you clearly separate the matching from the processing, the loop is just a simple dispatcher
Consider an interface:
class IMatchPattern
{
public:
virtual bool MatchesPattern(const Element& e) = 0;
};
Then you can organize a container of objects implementing IMatchPattern, to allow for iterative access to each pattern match method.
You can change your ExternalMatching to return bool, indicating that the processing has been done. This way the caller would be able to continue evaluating if necessary:
bool ExternalMatching(...)
{
if (MatchesPatternB(Element) {
// Act on it
// Remove Element from queue
return true;
}
return false;
}
Now you can call it like this:
if (ExternalMatchin1(...)) continue;
if (ExternalMatchin2(...)) continue;
...
if (ExternalMatchingN(...)) continue;
Ok, I ended up rewriting the loop more akin to this.
Huge thanks and credit goes to Yuushi, dasblinkenlight, David RodrÃguez for their help; this answer is based on a combination of their answers.
bool ExternalMatching(...)
{
bool Match;
if ((Match = MatchesPatternX(Element))) {
// Act on it
} else if ((Match = MatchesPatternY(Element))) {
// Act on it
}
return Match;
}
while (!Queue.empty())
{
auto & Element = Queue.front();
if (MatchesPatternA(Element)) { // Highest priority, since it's first
// Act on it
} else if (MatchesPatternB(Element)) {
// Act on it
} else if (ExternalMatching(...)) {
} else if (MatchesPatternC(Element)) { // Lowest priority, since it's last
// Act on it
}
// Remove Element from queue
}
Now, I know there's further room for improvement, see answers of Mateusz Pusz and Michael Sh. However, this is good enough to answer my original question, and it'll do for now. I'll consider improving it in the future.
If you're curious to see the real code (non-simplified version), see here:
https://github.com/shurcooL/Conception/blob/38f731ccc199d5391f46d8fce3cf9a9092f38c65/src/App.cpp#L592
Thanks everyone again!
I would like to suggest a Factory function that would take the Element and create an appropriate handler and return the interface pointer to the handler.
while (!Queue.empty())
{
auto & Element = *Queue.begin();
// get the appropriate handler object pointer e.g.
IPatternHandler *handler = Factory.GetHandler(Element);
handler->handle();
// clean up handler appropriately
}
My app consist of the main-process and two threads, all running concurrently and making use of three fifo-queues:
The fifo-q's are Qmain, Q1 and Q2. Internally the queues each use a counter that is incremented when an item is put into the queue, and decremented when an item is 'get'ed from the queue.
The processing involve two threads,
QMaster, which get from Q1 and Q2, and put into Qmain,
Monitor, which put into Q2,
and the main process, which get from Qmain and put into Q1.
The QMaster-thread loop consecutively checks the counts of Q1 and Q2 and if any items are in the q's, it get's them and puts them into Qmain.
The Monitor-thread loop obtains data from external sources, package it and put it into Q2.
The main-process of the app also runs a loop checking the count of Qmain, and if any items, get's an item
from Qmain at each iteration of the loop and process it further. During this processing it occasionally
puts an item into Q1 to be processed later (when it is get'ed from Qmain in turn).
The problem:
I've implemented all as described above, and it works for a randomly (short) time and then hangs.
I've managed to identify the source of the crashing to happen in the increment/decrement of the
count of a fifo-q (it may happen in any of them).
What I've tried:
Using three mutex's: QMAIN_LOCK, Q1_LOCK and Q2_LOCK, which I lock whenever any get/put operation
is done on a relevant fifo-q. Result: the app doesn't get going, just hangs.
The main-process must continue running all the time, must not be blocked on a 'read' (named-pipes fail, socketpair fail).
Any advice?
I think I'm not implementing the mutex's properly, how should it be done?
(Any comments on improving the above design also welcome)
[edit] below are the processes and the fifo-q-template:
Where & how in this should I place the mutex's to avoid the problems described above?
main-process:
...
start thread QMaster
start thread Monitor
...
while (!quit)
{
...
if (Qmain.count() > 0)
{
X = Qmain.get();
process(X)
delete X;
}
...
//at some random time:
Q2.put(Y);
...
}
Monitor:
{
while (1)
{
//obtain & package data
Q2.put(data)
}
}
QMaster:
{
while(1)
{
if (Q1.count() > 0)
Qmain.put(Q1.get());
if (Q2.count() > 0)
Qmain.put(Q2.get());
}
}
fifo_q:
template < class X* > class fifo_q
{
struct item
{
X* data;
item *next;
item() { data=NULL; next=NULL; }
}
item *head, *tail;
int count;
public:
fifo_q() { head=tail=NULL; count=0; }
~fifo_q() { clear(); /*deletes all items*/ }
void put(X x) { item i=new item(); (... adds to tail...); count++; }
X* get() { X *d = h.data; (...deletes head ...); count--; return d; }
clear() {...}
};
An example of how I would adapt the design and lock the queue access the posix way.
Remark that I would wrap the mutex to use RAII or use boost-threading and that I would use stl::deque or stl::queue as queue, but staying as close as possible to your code:
main-process:
...
start thread Monitor
...
while (!quit)
{
...
if (Qmain.count() > 0)
{
X = Qmain.get();
process(X)
delete X;
}
...
//at some random time:
QMain.put(Y);
...
}
Monitor:
{
while (1)
{
//obtain & package data
QMain.put(data)
}
}
fifo_q:
template < class X* > class fifo_q
{
struct item
{
X* data;
item *next;
item() { data=NULL; next=NULL; }
}
item *head, *tail;
int count;
pthread_mutex_t m;
public:
fifo_q() { head=tail=NULL; count=0; }
~fifo_q() { clear(); /*deletes all items*/ }
void put(X x)
{
pthread_mutex_lock(&m);
item i=new item();
(... adds to tail...);
count++;
pthread_mutex_unlock(&m);
}
X* get()
{
pthread_mutex_lock(&m);
X *d = h.data;
(...deletes head ...);
count--;
pthread_mutex_unlock(&m);
return d;
}
clear() {...}
};
Remark too that the mutex still needs to be initialized as in the example here and that count() should also use the mutex
Use the debugger. When your solution with mutexes hangs look at what the threads are doing and you will get a good idea about the cause of the problem.
What is your platform? In Unix/Linux you can use POSIX message queues (you can also use System V message queues, sockets, FIFOs, ...) so you don't need mutexes.
Learn about condition variables. By your description it looks like your Qmaster-thread is busy looping, burning your CPU.
One of your responses suggest you are doing something like:
Q2_mutex.lock()
Qmain_mutex.lock()
Qmain.put(Q2.get())
Qmain_mutex.unlock()
Q2_mutex.unlock()
but you probably want to do it like:
Q2_mutex.lock()
X = Q2.get()
Q2_mutex.unlock()
Qmain_mutex.lock()
Qmain.put(X)
Qmain_mutex.unlock()
and as Gregory suggested above, encapsulate the logic into the get/put.
EDIT: Now that you posted your code I wonder, is this a learning exercise?
Because I see that you are coding your own FIFO queue class instead of using the C++ standard std::queue. I suppose you have tested your class really well and the problem is not there.
Also, I don't understand why you need three different queues. It seems that the Qmain queue would be enough, and then you will not need the Qmaster thread that is indeed busy waiting.
About the encapsulation, you can create a synch_fifo_q class that encapsulates the fifo_q class. Add a private mutex variable and then the public methods (put, get, clear, count,...) should be like put(X) { lock m_mutex; m_fifo_q.put(X); unlock m_mutex; }
question: what would happen if you have more than one reader from the queue? Is it guaranteed that after a "count() > 0" you can do a "get()" and get an element?
I wrote a simple application below:
#include <queue>
#include <windows.h>
#include <process.h>
using namespace std;
queue<int> QMain, Q1, Q2;
CRITICAL_SECTION csMain, cs1, cs2;
unsigned __stdcall TMaster(void*)
{
while(1)
{
if( Q1.size() > 0)
{
::EnterCriticalSection(&cs1);
::EnterCriticalSection(&csMain);
int i1 = Q1.front();
Q1.pop();
//use i1;
i1 = 2 * i1;
//end use;
QMain.push(i1);
::LeaveCriticalSection(&csMain);
::LeaveCriticalSection(&cs1);
}
if( Q2.size() > 0)
{
::EnterCriticalSection(&cs2);
::EnterCriticalSection(&csMain);
int i1 = Q2.front();
Q2.pop();
//use i1;
i1 = 3 * i1;
//end use;
QMain.push(i1);
::LeaveCriticalSection(&csMain);
::LeaveCriticalSection(&cs2);
}
}
return 0;
}
unsigned __stdcall TMoniter(void*)
{
while(1)
{
int irand = ::rand();
if ( irand % 6 >= 3)
{
::EnterCriticalSection(&cs2);
Q2.push(irand % 6);
::LeaveCriticalSection(&cs2);
}
}
return 0;
}
unsigned __stdcall TMain(void)
{
while(1)
{
if (QMain.size() > 0)
{
::EnterCriticalSection(&cs1);
::EnterCriticalSection(&csMain);
int i = QMain.front();
QMain.pop();
i = 4 * i;
Q1.push(i);
::LeaveCriticalSection(&csMain);
::LeaveCriticalSection(&cs1);
}
}
return 0;
}
int _tmain(int argc, _TCHAR* argv[])
{
::InitializeCriticalSection(&cs1);
::InitializeCriticalSection(&cs2);
::InitializeCriticalSection(&csMain);
unsigned threadID;
::_beginthreadex(NULL, 0, &TMaster, NULL, 0, &threadID);
::_beginthreadex(NULL, 0, &TMoniter, NULL, 0, &threadID);
TMain();
return 0;
}
You should not lock second mutex when you already locked one.
Since the question is tagged with C++, I suggest to implement locking inside get/add logic of the queue class (e.g. using boost locks) or write a wrapper if your queue is not a class.
This allows you to simplify the locking logic.
Regarding the sources you have added: queue size check and following put/get should be done in one transaction otherwise another thread can edit the queue in between
Are you acquiring multiple locks simultaneously? This is generally something you want to avoid. If you must, ensure you are always acquiring the locks in the same order in each thread (this is more restrictive to your concurrency and why you generally want to avoid it).
Other concurrency advice: Are you acquiring the lock prior to reading the queue sizes? If you're using a mutex to protect the queues, then your queue implementation isn't concurrent and you probably need to acquire the lock before reading the queue size.
1 problem may occur due to this rule "The main-process must continue running all the time, must not be blocked on a 'read'". How did you implement it? what is the difference between 'get' and 'read'?
Problem seems to be in your implementation, not in the logic. And as you stated, you should not be in any dead lock because you are not acquiring another lock whether in a lock.