The average complexity of deterministic and randomized parallel comparison-sorting algorithms
In practice, the average time of (deterministic or randomized) sorting algorithms seems to be more relevant than the worst-case time of deterministic algorithms. Still, the many known complexity bounds for parallel comparison sorting include no nontrivial lower bounds for the average time required to sort by comparisons n elements with p processors (via deterministic or randomized algorithms). The authors show that for rho greater than or equal ton this time is THETA(log n/log (1 + rho/n))(it is easy to show that for rholess than or equal ton the time is THETA(n log n/rho) = THETA(log n/rho/n)). Therefore even the average-case behavior of randomized algorithms is not more efficient than the worst-case behavior of deterministic ones.
- Research Organization:
- Dept. of Mathematics, Sackler Faculty of Exact Sciences, Tel Aviv Univ., Tel Aviv (IL)
- OSTI ID:
- 6337973
- Journal Information:
- SIAM J. Comput.; (United States), Journal Name: SIAM J. Comput.; (United States) Vol. 17:6; ISSN SMJCA
- Country of Publication:
- United States
- Language:
- English
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