parallel processing
Parallel processing in computing refers to the method of running two or more processors (CPUs) to handle separate parts of an overall task, allowing for the simultaneous execution of multiple calculations or data processing tasks. This approach can significantly reduce the time required to run a program by dividing the task into multiple parts and assigning each part to a different processor. Systems that utilize parallel processing can include multi-core processors, which are integrated circuits containing two or more processors for enhanced performance, reduced power consumption, and more efficient simultaneous processing of multiple tasks[1][2].
Parallel processing is particularly useful for complex tasks and computations, such as those required in data science and artificial intelligence. By breaking down a large job into smaller jobs that are better suited to the number, size, and type of available processing units, parallel processing systems can complete tasks more quickly and efficiently. Each processor works on its assigned part of the task independently, and the results are then reassembled to solve the initial complex challenge[1][2][3].
The concept of parallel processing is not limited to multi-core processors within a single computer; it can also be applied to distributed systems where multiple computers are networked together to form virtual clusters, allowing for the leveraging of parallel processing power and storage options typically reserved for larger organizations[3].
Parallel processing contrasts with serial processing, where tasks are completed one at a time using a single processor. While serial processing is simpler and was the norm in early computing, parallel processing has become increasingly important with the advent of multicore processors and GPUs, which work together with CPUs to increase data throughput and the number of concurrent calculations within an application[2][3].
In summary, parallel processing is a critical aspect of modern computing that enables the efficient execution of complex and data-intensive tasks by utilizing the combined power of multiple processors, whether within a single computer or across a distributed network[1][2][3].
Citations:
[1] https://www.techtarget.com/searchdatacenter/definition/parallel-processing
[2] https://www.spiceworks.com/tech/iot/articles/what-is-parallel-processing/amp/
[3] https://www.heavy.ai/technical-glossary/parallel-computing
[4] https://www.verywellmind.com/what-is-parallel-processing-in-psychology-5195332
[5] https://en.wikipedia.org/wiki/Parallel_processing_(psychology)
[6] https://study.com/academy/lesson/what-is-parallel-processing-definition-model.html
[7] https://www.techopedia.com/definition/4598/parallel-processing