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In parallel programming, single tasks are split into a number of subtasks that can be computed relatively independently and then aggregated to form a single coherent solution. Parallel programming is most effective for tasks that can easily broken down into independent tasks such as purely mathematical problems, e.g. factorisation.

One way to achieve parallel programming is through distributed computing, which is a method of information processing in which work is performed by separate computers linked through a communications network.

Pioneers in the field of concurrent programming include Edsger Dijkstra and C. A. R. Hoare.

1 See also

• Critical sections
• Mutual exclusion
• Synchronization
• Computer multitasking
• Multithreading
• Concurrency control
• Coroutines
• Parallel processor
• Completion port s

2 External links

• Article "Multiprocessor Optimizations: Fine-Tuning Concurrent Access to Large Data Collections" by Ian Emmons
• Citations from CiteSeer