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

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

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。

并发性意味着同时执行多个任务，但不一定是同时执行。当你必须执行多个任务，但你只有一个资源时，我们就会追求并发性。在单核环境中，并发是通过上下文切换实现的。

并行性就像同时执行多个任务，就像你可以一边唱歌一边洗澡。现在你在并行地做这些任务。

术语异步与线程执行有关。在异步模型中，当执行一个任务时，您可以切换到另一个任务，而无需等待前一个任务完成。

异步编程帮助我们实现并发性。多线程环境中的异步编程是实现并行的一种方法。

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。