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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 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.
Even though it is very difficult to further speed up a single thread or single program, most computer systems are actually multitasking among multiple threads or programs. Thus, techniques that improve the throughput of all tasks result in overall performance gains. Two major techniques for throughput computing are multithreading and ...
The main challenge in designing concurrent programs is concurrency control: ensuring the correct sequencing of the interactions or communications between different computational executions, and coordinating access to resources that are shared among executions. [6] Potential problems include race conditions, deadlocks, and resource starvation.
Implementations of the fork–join model will typically fork tasks, fibers or lightweight threads, not operating-system-level "heavyweight" threads or processes, and use a thread pool to execute these tasks: the fork primitive allows the programmer to specify potential parallelism, which the implementation then maps onto actual parallel execution. [1]
With Stackless Python, a running program is split into microthreads that are managed by the language interpreter itself, not the operating system kernel—context switching and task scheduling is done purely in the interpreter (these are thus also regarded as a form of green thread). Microthreads manage the execution of different subtasks in a ...
This type of multitasking is called cooperative because all programs must cooperate for the scheduling scheme to work. In this scheme, the process scheduler of an operating system is known as a cooperative scheduler whose role is limited to starting the processes and letting them return control back to it voluntarily. [1] [2]