A complexity theory of efficient parallel algorithms
Theoretical Computer Science - Special issue: Fifteenth international colloquium on automata, languages and programming, Tampere, Finland, July 1988
A bridging model for parallel computation
Communications of the ACM
Fast parallel generation of random permutations
Proceedings of the 18th international colloquium on Automata, languages and programming
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SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
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HPCS '02 Proceedings of the 16th Annual International Symposium on High Performance Computing Systems and Applications
Engineering parallel in-place random generation of integer permutations
WEA'08 Proceedings of the 7th international conference on Experimental algorithms
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We show how to uniformly distribute data at random (not to be confounded with permutation routing) in a coarse grained parallel environment with p processors. In contrast to previously known work, our method is able to fulfill the three goals of uniformity, work-optimality and balance among the processors simultaneously. To guarantee the uniformity we investigate the matrix of communication requests between the processors. We show that its distribution is a generalization of the multivariate hypergeometric distribution and we give algorithms to compute it efficiently.