A complexity measure for data flow models
For common data flow schemes, the number of copies of tokens made during a computation is demonstrated to be a Blum (1967) complexity measure. Results from abstract complexity theory then hold for the copy measure, suggesting, for example, that any implementation of a data flow processor will be lim...
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| Veröffentlicht in: | International Journal of Computer & Information Sciences 1985-04, Vol.14 (2), p.107-122 |
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| container_title | International Journal of Computer & Information Sciences |
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| creator | MOTTELER, H. E SMITH, C. H |
| description | For common data flow schemes, the number of copies of tokens made during a computation is demonstrated to be a Blum (1967) complexity measure. Results from abstract complexity theory then hold for the copy measure, suggesting, for example, that any implementation of a data flow processor will be limited by its ability to copy tokens. The copy measure is a natural measure of complexity for data flow calculations, and is distinct from the usual time or space measures. The result is generalized to a broader class of data flow schemas, including those with an apply operator. An example is also presented of a data flow scheme that makes no copies either by explicit copy nodes or by operators that release more than one token at a time. Calculation in this example proceeds by the repeated modification of a single token. |
| doi_str_mv | 10.1007/BF00996925 |
| format | Article |
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| ispartof | International Journal of Computer & Information Sciences, 1985-04, Vol.14 (2), p.107-122 |
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| language | eng |
| recordid | cdi_proquest_journals_204320425 |
| source | SpringerNature Journals |
| subjects | Applied sciences Computer programming Computer science control theory systems Exact sciences and technology Miscellaneous Software Theory |
| title | A complexity measure for data flow models |
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