In parallel computing, an embarrassingly parallel workload (or embarrassingly parallel problem) is one for which little or no effort is required to separate the problem into a number of parallel tasks. This is often the case where there exists no dependency (or communication) between those parallel tasks.
Embarrassingly parallel problems tend to require little or no communication of results between tasks, and are thus different from distributed computing problems that require communication between tasks, especially communication of intermediate results. They are easy to perform on server farms which do not have any of the special infrastructure used in a true supercomputer cluster. They are thus well suited to large, internet based distributed platforms such as BOINC.
A common example of an embarrassingly parallel problem lies within graphics processing units (GPUs) for tasks such as 3D projection, where each pixel on the screen may be rendered independently.
Read more about Embarrassingly Parallel: Examples, Implementations
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