Inparallel computing, anembarrassingly parallel workload or problem (also calledembarrassingly parallelizable,perfectly parallel,delightfully parallel orpleasingly parallel) is one where little or no effort is needed to split the problem into a number of parallel tasks.[1] This is due to minimal or no dependency upon communication between the parallel tasks, or for results between them.[2]
These differ fromdistributed computing problems, which need communication between tasks, especially communication of intermediate results. They are easier to perform onserver farms which lack the special infrastructure used in a truesupercomputer cluster. They are well-suited to large, Internet-basedvolunteer computing platforms such asBOINC, and suffer less fromparallel slowdown. The opposite of embarrassingly parallel problems areinherently serial problems, which cannot be parallelized at all.
A common example of an embarrassingly parallel problem is 3D video rendering handled by agraphics processing unit, where each frame (forward method) or pixel (ray tracing method) can be handled with no interdependency.[3] Some forms ofpassword cracking are another embarrassingly parallel task that is easily distributed oncentral processing units,CPU cores, or clusters.
"Embarrassingly" is used here to refer to parallelization problems which are "embarrassingly easy".[4] The term may imply embarrassment on the part of developers or compilers: "Because so many important problems remain unsolved mainly due to their intrinsic computational complexity, it would be embarrassing not to develop parallel implementations of polynomialhomotopy continuation methods."[5] The term is first found in the literature in a 1986 book on multiprocessors byMATLAB's creatorCleve Moler,[6] who claims to have invented the term.[7]
An alternative term,pleasingly parallel, has gained some use, perhaps to avoid the negative connotations of embarrassment in favor of a positive reflection on the parallelizability of the problems: "Of course, there is nothing embarrassing about these programs at all."[8]
A trivial example involves serving static data. It would take very little effort to have many processing units produce the same set of bits. Indeed, the famousHello World problem could easily be parallelized with few programming considerations or computational costs.
Some examples of embarrassingly parallel problems include:
Some computational problems are "embarrassingly parallel": they can easily be divided into components that can be executed concurrently.
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