![]() In contrast, in concurrent computing, the various processes often do not address related tasks when they do, as is typical in distributed computing, the separate tasks may have a varied nature and often require some inter-process communication during execution. In parallel computing, a computational task is typically broken down into several, often many, very similar sub-tasks that can be processed independently and whose results are combined afterwards, upon completion. Parallel computing is closely related to concurrent computing-they are frequently used together, and often conflated, though the two are distinct: it is possible to have parallelism without concurrency, and concurrency without parallelism (such as multitasking by time-sharing on a single-core CPU). As power consumption (and consequently heat generation) by computers has become a concern in recent years, parallel computing has become the dominant paradigm in computer architecture, mainly in the form of multi-core processors. Parallelism has long been employed in high-performance computing, but has gained broader interest due to the physical constraints preventing frequency scaling. There are several different forms of parallel computing: bit-level, instruction-level, data, and task parallelism. Large problems can often be divided into smaller ones, which can then be solved at the same time. ![]() Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. ![]() Programming paradigm in which many processes are executed simultaneously IBM's Blue Gene/P massively parallel supercomputer Programming paradigms
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