Having built a Beowulf cluster using instructions found on the Internet or in popular magazines, some zealous individuals are disgusted to discover that their favorite word processor and spreadsheet packages will not run on their powerful new creation.
Having built a Beowulf cluster using instructions found on the Internet or in popular magazines, some zealous individuals are disgusted to discover that their favorite word processor and spreadsheet packages will not run on their powerful new creation.
This is the case because unless a particular application has been specifically programmed to use multiple processors, it must be rewritten, or parallelized, before it will be able to run on either a parallel supercomputer or a cluster of PCs. Moreover, since Beowulf clusters consist of computational and network elements that may be combined to optimally solve a particular problem or run a particular algorithm, the target application should play a significant role in the design of any new cluster.
Parallel computing is accomplished by splitting up a large computational problem into smaller tasks that may be performed simultaneously by multiple processors. For example, the addition of two very long vectors of numbers, A and B, can be performed by two processors if one of them adds the first half of vector A to the first half of vector B, while the second adds the second half of vector A to the second half of vector B. While this theoretically halves the time needed to solve the problem, the resulting vector, C, is now split across two different processor memories.
Because of this split, communication must occur to get the entire solution in one place. The distribution of the initial data, A and B, and the collection…
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