我能想到的最简单的例子是使递增成为一个原子操作。

使用标准int型:

private volatile int counter;

public int getNextUniqueIndex() {
    return counter++; // Not atomic, multiple threads could get the same result
}

AtomicInteger:

private AtomicInteger counter;

public int getNextUniqueIndex() {
    return counter.getAndIncrement();
}

后者是执行简单的突变效果(特别是计数或唯一索引)的一种非常简单的方法，而不必求助于同步所有访问。

More complex synchronization-free logic can be employed by using compareAndSet() as a type of optimistic locking - get the current value, compute result based on this, set this result iff value is still the input used to do the calculation, else start again - but the counting examples are very useful, and I'll often use AtomicIntegers for counting and VM-wide unique generators if there's any hint of multiple threads being involved, because they're so easy to work with I'd almost consider it premature optimisation to use plain ints.

While you can almost always achieve the same synchronization guarantees with ints and appropriate synchronized declarations, the beauty of AtomicInteger is that the thread-safety is built into the actual object itself, rather than you needing to worry about the possible interleavings, and monitors held, of every method that happens to access the int value. It's much harder to accidentally violate threadsafety when calling getAndIncrement() than when returning i++ and remembering (or not) to acquire the correct set of monitors beforehand.

Atomic classes are not general purpose replacements for java.lang.Integer and related classes. They do not define methods such as equals, hashCode and compareTo. (Because atomic variables are expected to be mutated, they are poor choices for hash table keys.) Additionally, classes are provided only for those types that are commonly useful in intended applications. For example, there is no atomic class for representing byte. In those infrequent cases where you would like to do so, you can use an AtomicInteger to hold byte values, and cast appropriately. You can also hold floats using Float.floatToRawIntBits(float) and Float.intBitsToFloat(int) conversions, and doubles using Double.doubleToRawLongBits(double) and Double.longBitsToDouble(long) conversions.

参考:https://docs.oracle.com/javase/8/docs/api/java/util/concurrent/atomic/package-summary.html

我使用AtomicInteger来解决就餐哲学家的问题。

在我的解决方案中，使用AtomicInteger实例来表示fork，每个哲学家需要两个。每个哲学家都被标识为一个整数，从1到5。当一个哲学家使用一个fork时，AtomicInteger保存哲学家的值，从1到5，否则该fork没有被使用，因此AtomicInteger的值为-1。

AtomicInteger允许在一个原子操作中检查一个fork是否空闲，value==-1，如果空闲则将其设置为fork的所有者。参见下面的代码。

AtomicInteger fork0 = neededForks[0];//neededForks is an array that holds the forks needed per Philosopher
AtomicInteger fork1 = neededForks[1];
while(true){    
    if (Hungry) {
        //if fork is free (==-1) then grab it by denoting who took it
        if (!fork0.compareAndSet(-1, p) || !fork1.compareAndSet(-1, p)) {
          //at least one fork was not succesfully grabbed, release both and try again later
            fork0.compareAndSet(p, -1);
            fork1.compareAndSet(p, -1);
            try {
                synchronized (lock) {//sleep and get notified later when a philosopher puts down one fork                    
                    lock.wait();//try again later, goes back up the loop
                }
            } catch (InterruptedException e) {}

        } else {
            //sucessfully grabbed both forks
            transition(fork_l_free_and_fork_r_free);
        }
    }
}

因为compareAndSet方法不阻塞，它应该增加吞吐量，完成更多的工作。正如你所知道的，Dining Philosophers问题是在需要对资源进行受控访问时使用的，即需要fork，就像一个进程需要资源来继续工作一样。

AtomicInteger的主要用途是在多线程上下文中，并且需要在不使用synchronized的情况下对整数执行线程安全操作。基本类型int上的赋值和检索已经是原子的，但AtomicInteger附带的许多操作在int上不是原子的。

最简单的是getAndXXX或xXXAndGet。例如，getAndIncrement()是i++的原子等价物，它不是原子的，因为它实际上是三个操作的捷径:检索、加法和赋值。compareAndSet对于实现信号量、锁、锁存器等非常有用。

使用AtomicInteger比使用同步执行相同的操作更快，可读性更强。

一个简单的测试:

public synchronized int incrementNotAtomic() {
    return notAtomic++;
}

public void performTestNotAtomic() {
    final long start = System.currentTimeMillis();
    for (int i = 0 ; i < NUM ; i++) {
        incrementNotAtomic();
    }
    System.out.println("Not atomic: "+(System.currentTimeMillis() - start));
}

public void performTestAtomic() {
    final long start = System.currentTimeMillis();
    for (int i = 0 ; i < NUM ; i++) {
        atomic.getAndIncrement();
    }
    System.out.println("Atomic: "+(System.currentTimeMillis() - start));
}

在我使用Java 1.6的PC上，原子测试在3秒内运行，而同步测试在5.5秒内运行。这里的问题是同步操作(notatomic++)非常短。所以同步的成本相对于操作来说是非常重要的。

除了原子性，AtomicInteger还可以作为一个可变版本的Integer，例如在map中作为值使用。

可以在原子整数或长值上使用compareAndSwap (CAS)实现非阻塞锁。“Tl2”软件事务内存论文这样描述:

我们将一个特殊版本的写锁与每个事务关联起来 内存位置。在其最简单的形式中，版本化写锁是 使用CAS操作获取锁和的单字自旋锁 一个发布它的商店。因为我们只需要一个比特来表示 如果锁已被占用，则使用锁字的其余部分来保存 版本号。

What it is describing is first read the atomic integer. Split this up into an ignored lock-bit and the version number. Attempt to CAS write it as the lock-bit cleared with the current version number to the lock-bit set and the next version number. Loop until you succeed and your are the thread which owns the lock. Unlock by setting the current version number with the lock-bit cleared. The paper describes using the version numbers in the locks to coordinate that threads have a consistent set of reads when they write.

本文介绍了处理器对比较和交换操作的硬件支持，这使得比较和交换操作非常高效。它还声称:

使用原子变量的非阻塞基于cas的计数器有更好的性能 在低到中等争用情况下，性能优于基于锁的计数器

如果您查看AtomicInteger具有的方法，您将注意到它们倾向于对应于对int的常见操作。例如:

static AtomicInteger i;

// Later, in a thread
int current = i.incrementAndGet();

是线程安全的版本:

static int i;

// Later, in a thread
int current = ++i;

方法映射如下: ++i是i. incrementandget () i++就是i. getandincrement () ——i是i. decrementandget () i——是i. getanddecrement () I = x = I .set(x) X = I = X = I .get()

还有其他方便的方法，如compareAndSet或addAndGet