We show how to distribute data at random (not to be confounded with permutation routing) in a coarse grained parallel environment with $p$ processors. Previously known methods were not able to fulfill the three criteria 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 give algorithms to compute it efficiently
Many papers on parallel random permutation algorithms assume the input size n to be a power of two a...
We consider the problem of generating random permutations with the uniform distribution. That is, w...
The technique of randomization has been employed to solve numerous prob lems of computing both sequ...
International audienceWe show how to uniformly distribute data at random (not to be confounded with ...
International audienceWe show how to uniformly distribute data at random (not to be confounded with ...
In [\cite{GUSTEDT:2006:INRIA-00000900:2}] we have shown that random shuffling of data can be realise...
International audienceWe tackle the feasibility and efficiency of two new parallel algorithms that s...
This paper describes deterministic communication-efficient algorithms for performing random data acc...
In this paper, we consider the problem of selection on coarse-grained distributed memory parallel co...
A behavioural theory comprises a set of postulates that characterise a particular class of algorith...
We compare parallel algorithms for random permutation generation on symmetric multiprocessors (SMPs...
Shuffling is the process of placing elements into a random order such that any permutation occurs wi...
An algorithm for parallel generation of a random permutation of a large set of distinct integers is ...
Abstract. Random networks are widely used for modeling and analyz-ing complex processes. Many mathem...
This dissertation focuses on scalable parallel algorithms for irregular communication, random data a...
Many papers on parallel random permutation algorithms assume the input size n to be a power of two a...
We consider the problem of generating random permutations with the uniform distribution. That is, w...
The technique of randomization has been employed to solve numerous prob lems of computing both sequ...
International audienceWe show how to uniformly distribute data at random (not to be confounded with ...
International audienceWe show how to uniformly distribute data at random (not to be confounded with ...
In [\cite{GUSTEDT:2006:INRIA-00000900:2}] we have shown that random shuffling of data can be realise...
International audienceWe tackle the feasibility and efficiency of two new parallel algorithms that s...
This paper describes deterministic communication-efficient algorithms for performing random data acc...
In this paper, we consider the problem of selection on coarse-grained distributed memory parallel co...
A behavioural theory comprises a set of postulates that characterise a particular class of algorith...
We compare parallel algorithms for random permutation generation on symmetric multiprocessors (SMPs...
Shuffling is the process of placing elements into a random order such that any permutation occurs wi...
An algorithm for parallel generation of a random permutation of a large set of distinct integers is ...
Abstract. Random networks are widely used for modeling and analyz-ing complex processes. Many mathem...
This dissertation focuses on scalable parallel algorithms for irregular communication, random data a...
Many papers on parallel random permutation algorithms assume the input size n to be a power of two a...
We consider the problem of generating random permutations with the uniform distribution. That is, w...
The technique of randomization has been employed to solve numerous prob lems of computing both sequ...