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Multiprocessing however means true parallel execution of multiple processes using more than one processor. [7] Multiprocessing doesn't necessarily mean that a single process or task uses more than one processor simultaneously; the term parallel processing is generally used to denote that scenario. [6]
In this way, multiple processes are part-way through execution at a single instant, but only one process is being executed at that instant. [citation needed] Concurrent computations may be executed in parallel, [3] [6] for example, by assigning each process to a separate processor or processor core, or distributing a computation across a network.
However, in multiprocessing systems many processes may run off of, or share, the same reentrant program at the same location in memory, but each process is said to own its own image of the program. Processes are often called "tasks" in embedded operating systems. The sense of "process" (or task) is "something that takes up time", as opposed to ...
A process with two threads of execution, running on a single processor . In computer architecture, multithreading is the ability of a central processing unit (CPU) (or a single core in a multi-core processor) to provide multiple threads of execution.
Task parallelism focuses on distributing tasks—concurrently performed by processes or threads—across different processors. In contrast to data parallelism which involves running the same task on different components of data, task parallelism is distinguished by running many different tasks at the same time on the same data. [1]
The term "multiprocessor" can be confused with the term "multiprocessing". While multiprocessing is a type of processing in which two or more processors work together to execute multiple programs simultaneously, multiprocessor refers to a hardware architecture that allows multiprocessing. [5]
As multitasking greatly improved the throughput of computers, programmers started to implement applications as sets of cooperating processes (e. g., one process gathering input data, one process processing input data, one process writing out results on disk). This, however, required some tools to allow processes to efficiently exchange data.
Since the two processors work in parallel, the job of performing array addition would take one half the time of performing the same operation in serial using one CPU alone. The program expressed in pseudocode below—which applies some arbitrary operation, foo , on every element in the array d —illustrates data parallelism: [ nb 1 ]