每个人都很难将异步与并行或并发相关联，因为异步既不是并行的反义词，也不是并发的反义词。它是同步的反义词。它只是表示某些东西，在这个例子中是线程，是否会与其他东西同步，在这个例子中是另一个线程。

总结

并发(Concurrent):多件事情似乎同时发生(具有在并发任务之间快速切换的能力;它们是并发的，因为每个任务都想要一块资源，CPU等等。)

并行是指同时发生多件事情(执行线程的数量与执行内核的数量密切相关)

异步是简单的非阻塞，当我们必须等待的事情不会让我们忙于等待(需要某种通知机制从我们离开的地方继续)

并发性可能发生在以下几种场景中:

异步——这意味着你的程序执行非阻塞操作。例如，它可以通过HTTP发起对远程资源的请求，然后在等待接收响应的同时继续执行一些其他任务。这有点像你发了一封电子邮件，然后继续你的生活，没有等待回复。

并行性——这意味着您的程序利用多核机器的硬件，通过将工作分解为任务，在同一时间执行任务，每个任务都在单独的核心上执行。这有点像洗澡时唱歌:你实际上是在同时做两件事。

多线程——这是一种允许不同线程并发执行的软件实现。多线程程序似乎同时在做几件事，即使它运行在单核机器上。这有点像通过各种IM窗口与不同的人聊天;虽然你实际上是在来回切换，但最终结果是你同时进行了多个对话。

Parallel : It's a broad term that means that two pieces of code execute that "at the same time". It doesn't matter if it's "real" parallelism or if it's faked through some clever design pattern. The point is that you can start the "tasks" at the same time and then control them separately (with mutex and all the appropriate tricks). But usually you prefer to use the word "parallel" only for "true" parallelism, as in : you make it happen through non-cooperative multitasking (whether be throuch CPU/GPU cores, or only at software level by letting the OS managing it at a very low level). People are reluctant to say "parallel" just for complicated sequential code that fakes parallelism, like you would find in a browser window's javascript for example. Hence the reason why people in this thread say "asynchronous has nothing to do with parallelism". Well it does, but just don't confuse them.

并发:没有并行性就不可能有并发性(无论是模拟的还是真实的，正如我上面解释的那样)，但是这个术语特别关注的是两个系统将试图在某个时间点同时访问同一资源的事实。它强调了一个事实，那就是你必须要处理这个问题。

异步:每个人都说异步与并行无关，这是对的，但它为并行铺平了道路(让事情并行或不并行的负担在你身上——继续阅读)。

“异步”指的是并行性的一种表示形式，它形式化了并行性中通常涉及的三个基本内容:1)定义任务的初始化(比如它何时开始以及它获得哪些参数)，2)任务完成后必须做什么，3)代码在此期间应该继续做什么。

但它仍然只是语法(通常表示为回调方法)。在后台，底层系统可能简单地认为这些所谓的“任务”只是堆积起来的代码片段，直到它完成当前正在执行的代码。然后它一个接一个地把它们拆开，然后依次执行。与否。它还可以为每个任务创建一个线程，并并行运行它们。谁在乎呢?这部分不包括在概念中;)

并发是指多个任务的执行是交错的，而不是每个任务依次执行。

并行性是指这些任务实际上是并行执行的。

异步是一个单独的概念(尽管在某些上下文中是相关的)。它指的是一个事件可能发生在与另一个事件不同的时间(不同步)。下面的图表说明了同步执行和异步执行之间的区别，其中参与者可以对应于不同的线程、进程甚至服务器。

Concurrency Concurrency means that an application is making progress on more than one task at the same time (concurrently). Well, if the computer only has one CPU the application may not make progress on more than one task at exactly the same time, but more than one task is being processed at a time inside the application. It does not completely finish one task before it begins the next. Parallelism Parallelism means that an application splits its tasks up into smaller subtasks which can be processed in parallel, for instance on multiple CPUs at the exact same time. Concurrency vs. Parallelism In Detail As you can see, concurrency is related to how an application handles multiple tasks it works on. An application may process one task at at time (sequentially) or work on multiple tasks at the same time (concurrently). Parallelism on the other hand, is related to how an application handles each individual task. An application may process the task serially from start to end, or split the task up into subtasks which can be completed in parallel. As you can see, an application can be concurrent, but not parallel. This means that it processes more than one task at the same time, but the tasks are not broken down into subtasks. An application can also be parallel but not concurrent. This means that the application only works on one task at a time, and this task is broken down into subtasks which can be processed in parallel. Additionally, an application can be neither concurrent nor parallel. This means that it works on only one task at a time, and the task is never broken down into subtasks for parallel execution. Finally, an application can also be both concurrent and parallel, in that it both works on multiple tasks at the same time, and also breaks each task down into subtasks for parallel execution. However, some of the benefits of concurrency and parallelism may be lost in this scenario, as the CPUs in the computer are already kept reasonably busy with either concurrency or parallelism alone. Combining it may lead to only a small performance gain or even performance loss. Make sure you analyze and measure before you adopt a concurrent parallel model blindly.

从http://tutorials.jenkov.com/java-concurrency/concurrency-vs-parallelism.html