Parallel algorithm

In computer science, a parallel algorithm, as opposed to a traditional serial algorithm, is an algorithm which can do multiple operations in a given time. It has been a tradition of computer science to describe serial algorithms in abstract machine models, often the one known as random-access machine. Similarly, many computer science researchers have used a so-called parallel random-access machine (PRAM) as a parallel abstract machine (shared-memory).

Many parallel algorithms are executed concurrently – though in general concurrent algorithms are a distinct concept – and thus these concepts are often conflated, with which aspect of an algorithm is parallel and which is concurrent not being clearly distinguished. Further, non-parallel, non-concurrent algorithms are often referred to as "sequential algorithms", by contrast with concurrent algorithms.

Another problem with parallel algorithms is ensuring that they are suitably load balanced, by ensuring that load (overall work) is balanced, rather than input size being balanced. For example, checking all numbers from one to a hundred thousand for primality is easy to split among processors; however, if the numbers are simply divided out evenly (1–1,000, 1,001–2,000, etc.), the amount of work will be unbalanced, as smaller numbers are easier to process by this algorithm (easier to test for primality), and thus some processors will get more work to do than the others, which will sit idle until the loaded processors complete.

1. ↑ Blelloch, Guy E.; Maggs, Bruce M. "Parallel Algorithms" (PDF). USA: School of Computer Science, Carnegie Mellon University. Retrieved 2015-07-27.
2. ↑ Kurgalin, Sergei; Borzunov, Sergei (2020). The discrete math workbook: a companion manual using Python. Texts in Computer Science (2nd ed.). Cham, Switzerland: Springer Naturel. ISBN 978-3-030-42220-2.
3. ↑ Hagit Attiya and Jennifer Welch. Distributed Computing: Fundamentals, Simulations, and Advanced Topics. 2nd ed., Wiley, 2004.