Asymptotically Optimal Probabilistic Embedding Algorithms for Supporting Tree Structured Computations in Hypercubes

Authors:
Keqin Li;John E. Dorband
Affiliations:
-;-
Venue:
FRONTIERS '99 Proceedings of the The 7th Symposium on the Frontiers of Massively Parallel Computation
Year:
1999

Citing 0
Cited 3

Performance Evaluation of a Random-Walk-Based Algorithm for Embedding Dynamically Evolving Trees in Butterflies

IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Analysis of randomized load distribution for reproduction trees in linear arrays and rings

Theoretical Computer Science
Design and analysis of asymptotically optimal randomized tree embedding algorithms in static networks

Performance Evaluation - Performance modelling and evaluation of high-performance parallel and distributed systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

We show two asymptotically optimal probabilistic tree embedding algorithms in hypercubes with constant dilation. These algorithms are slight extension of the random walk algorithm. The first algorithm allows a tree node to have a stay option during each step of a random walk. The second algorithm permits varying length of random walks. Numerical data are given to demonstrate performance improvement.