A second way to eliminate the problem of tasks colliding
over shared resources is to eliminate the sharing of variables, which can be
done by creating different storage for the same variable, for each different
thread that uses an object. Thus, if you have five threads using an object with
a variable x, thread local storage automatically generates five
different pieces of storage for x. Fortunately, the creation and
management of thread local storage is taken care of automatically by ZThread s ThreadLocal
template, as seen here:
//: C11:ThreadLocalVariables.cpp {RunByHand}
// Automatically giving each thread its own storage.
//{L} ZThread
#include <iostream>
#include "zthread/Thread.h"
#include "zthread/Mutex.h"
#include "zthread/Guard.h"
#include "zthread/ThreadedExecutor.h"
#include "zthread/Cancelable.h"
#include "zthread/ThreadLocal.h"
#include "zthread/CountedPtr.h"
using namespace ZThread;
using namespace std;
class ThreadLocalVariables : public Cancelable {
ThreadLocal<int> value;
bool canceled;
Mutex lock;
public:
ThreadLocalVariables() : canceled(false) {
value.set(0);
}
void increment() { value.set(value.get() + 1); }
int get() { return value.get(); }
void cancel() {
Guard<Mutex> g(lock);
canceled = true;
}
bool isCanceled() {
Guard<Mutex> g(lock);
return canceled;
}
};
class Accessor : public Runnable {
int id;
CountedPtr<ThreadLocalVariables> tlv;
public:
Accessor(CountedPtr<ThreadLocalVariables>&
tl, int idn)
: id(idn), tlv(tl) {}
void run() {
while(!tlv->isCanceled()) {
tlv->increment();
cout << *this << endl;
}
}
friend ostream&
operator<<(ostream& os, Accessor& a)
{
return os << "#" << a.id
<< ": " << a.tlv->get();
}
};
int main() {
cout << "Press <Enter> to quit"
<< endl;
try {
CountedPtr<ThreadLocalVariables>
tlv(new ThreadLocalVariables);
const int SZ = 5;
ThreadedExecutor executor;
for(int i = 0; i < SZ; i++)
executor.execute(new
Accessor(tlv, i));
cin.get();
tlv->cancel(); // All Accessors will quit
} catch(Synchronization_Exception& e) {
cerr << e.what() << endl;
}
} ///:~
When you run this program, you ll see evidence that the
individual threads are each allocated their own storage.
