Name
Abstract | ||
|---|---|---|
In this paper we face the problem of determining the best partial order among the subgoals of a query in order for this query to be evaluated under Independent AND Parallelism. This is the most common source of parallelism exploited by the different models that have been proposed to evaluate logic programs in parallel. This problem is proved to be NP-hard, so every model utilises its own heuristic strategy in order to estimate the best ordering. Here, a Genetic approach is proposed and compared to conventional heuristic ones. The experimental results show that the Genetic Algorithm produces better solutions, as well as comparable execution times for reasonably sized problems. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1007/BFb0032516 | IWANN |
Keywords | Field | DocType |
parallel logic programming,evolutive optimization.,genetic algorithms,genetic approach,independent and parallelism,computing independent,logic programs,genetics,genetic algorithm,partial order | Heuristic,Parallel logic programming,Task parallelism,Computer science,Theoretical computer science,Data parallelism,Genetic representation,Genetic algorithm | Conference |
Volume | ISSN | ISBN |
1240 | 0302-9743 | 3-540-63047-3 |
Citations | PageRank | References |
3 | 0.46 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Camino R. Vela | 1 | 346 | 31.00 |
| Cesar Alonso | 2 | 60 | 8.45 |
| Ramiro Varela | 3 | 301 | 29.96 |
| Jorge Puente | 4 | 9 | 2.89 |