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Parallel computing. Large supercomputers such as IBM's Blue Gene/P are designed to heavily exploit parallelism. Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. [1] Large problems can often be divided into smaller ones, which can then be solved at the same time.
Parallel running. The old and new systems are doing the same processing and operating side by side. Parallel running is a strategy for system changeover where a new system slowly assumes the roles of the older system while both systems operate simultaneously. [1][2] This conversion takes place as the technology of the old system is outdated so ...
From the software standpoint, hardware support for multithreading is more visible to software, requiring more changes to both application programs and operating systems than multiprocessing. Hardware techniques used to support multithreading often parallel the software techniques used for computer multitasking. Thread scheduling is also a major ...
Parallel communication is and always has been widely used within integrated circuits, in peripheral buses, and in memory devices such as RAM. Computer system buses, on the other hand, have evolved over time: parallel communication was commonly used in earlier system buses, whereas serial communications are prevalent in modern computers.
The same system may be characterized both as "parallel" and "distributed"; the processors in a typical distributed system run concurrently in parallel. [22] Parallel computing may be seen as a particularly tightly coupled form of distributed computing, [23] and distributed computing may be seen as a loosely coupled form of parallel computing. [12]
Data parallelism is parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different nodes, which operate on the data in parallel. It can be applied on regular data structures like arrays and matrices by working on each element in parallel. It contrasts to task parallelism as ...
Concurrency (computer science) In computer science, concurrency is the ability of different parts or units of a program, algorithm, or problem to be executed out-of-order or in partial order, without affecting the outcome. This allows for parallel execution of the concurrent units, which can significantly improve overall speed of the execution ...
In political science, parallel voting or superposition refers to the use of two or more electoral systems to elect different members of a legislature. More precisely, an electoral system is a superposition if it is a mixture of at least two tiers, which do not interact with each other in any way; one part of a legislature is elected using one method, while another part is elected using a ...