Parallelism in computing refers to techniques that make a program faster by doing many – hundreds to millions – of operations simultaneously. It is a foundational principle of distributed computing, machine learning, and multithreaded programming because it enables programmers, data teams, and applications to tackle large problems by breaking them down into smaller, independent tasks. It often requires hardware large collections of low cost hardware whether it be multicore processors or servers in a cluster.

There are several advantages to parallelism in computing. It can be less costly and less time-consuming because several resources are working together at one time. In addition, it can be more practical to solve large problems by breaking them down into smaller pieces.

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