|Afilliation||High Performance Computing, Center for Biomedical Computing (SFF), Scientific Computing|
|Project(s)||Center for Biomedical Computing (SFF)|
|Publication Type||Book Chapter|
|Year of Publication||2015|
|Book Title||Encyclopedia of Applied and Computational Mathematics|
|Publisher||Springer Berlin Heidelberg|
Parallel computing can be understood as solving a computational problem through collaborative use of multiple resources that belong to a parallel computer system. Here, a parallel system can be anything between a single multiprocessor machine and an Internet-connected cluster that is made up of hybrid compute nodes. There are two main motivations for adopting parallel computations. The first motivation is about reducing the computational time, because employing more computational units for solving a same problem usually results in lower wall-time usage. The second – and perhaps more important – motivation is the wish of obtaining more details, which can arise from higher temporal and spatial resolutions, more advanced mathematical and numerical models, and more realizations.