Concurrency

New, asynchronous "shared-nothing" platforms and APIs like Vert.x and Play / Akka and Qbit have emerged. These platforms use a different concurrency model than the standard Java / JEE concurrency model of threading, shared memory and locking. New non-blocking concurrency algorithms have been published, and new non-blocking tools like the LMax Disrupter have been added to our toolkits. New functional programming parallelism has been introduced with the Fork and Join framework in Java 7, and the collection streams API in Java 8.

More complex design: Though some parts of a multithreaded applications is simpler than a singlethreaded application, other parts are more complex. Code executed by multiple threads accessing shared data need special attention. Thread interaction is far from always simple. Errors arising from incorrect thread synchronization can be very hard to detect, reproduce and fix.
Context Switching Overhead: When a CPU switches from executing one thread to executing another, the CPU needs to save the local data, program pointer etc. of the current thread, and load the local data, program pointer etc. of the next thread to execute. This switch is called a "context switch". The CPU switches from executing in the context of one thread to executing in the context of another. Context switching isn't cheap. You don't want to switch between threads more than necessary.
Increased Resource Consumption: A thread needs some resources from the computer in order to run. Besides CPU time a thread needs some memory to keep its local stack. It may also take up some resources inside the operating system needed to manage the thread.

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.
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.

There are no rules about which of the two methods that is the best. Both methods works. Personally though, I prefer implementing Runnable, and handing an instance of the implementation to a Thread instance. When having the Runnable's executed by a thread pool it is easy to queue up the Runnable instances until a thread from the pool is idle. This is a little harder to do with Thread subclasses. Sometimes you may have to implement Runnable as well as subclass Thread. For instance, if creating a subclass of Thread that can execute more than one Runnable. This is typically the case when implementing a thread pool.

Difference between Callable and Runnable interface.

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