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A concurrent programming language is defined as one which uses the concept of simultaneously executing processes or threads of execution as a means of structuring a program. A parallel language is able to express programs that are executable on more than one processor.
In a multiprocessor system, task parallelism is achieved when each processor executes a different thread (or process) on the same or different data. The threads may execute the same or different code. In the general case, different execution threads communicate with one another as they work, but this is not a requirement. Communication usually ...
A number of different methods can be used to implement concurrent programs, such as implementing each computational execution as an operating system process, or implementing the computational processes as a set of threads within a single operating system process.
A major area of research is the thread scheduler that must quickly choose from among the list of ready-to-run threads to execute next, as well as maintain the ready-to-run and stalled thread lists. An important subtopic is the different thread priority schemes that can be used by the scheduler.
Cooperative multitasking is similar to async/await in languages, such as JavaScript or Python, that feature a single-threaded event-loop in their runtime. This contrasts with cooperative multitasking in that await cannot be invoked from a non-async function, but only an async function, which is a kind of coroutine .
A task-parallel model focuses on processes, or threads of execution. These processes will often be behaviourally distinct, which emphasises the need for communication. Task parallelism is a natural way to express message-passing communication. In Flynn's taxonomy, task parallelism is usually classified as MIMD/MPMD or MISD.
One benefit of a thread pool over creating a new thread for each task is that thread creation and destruction overhead is restricted to the initial creation of the pool, which may result in better performance and better system stability. Creating and destroying a thread and its associated resources can be an expensive process in terms of time.
Thread safe, MT-safe: Use a mutex for every single resource to guarantee the thread to be free of race conditions when those resources are accessed by multiple threads simultaneously. Thread safety guarantees usually also include design steps to prevent or limit the risk of different forms of deadlocks , as well as optimizations to maximize ...