The effect of range and bandwidth on the round complexity in the congested clique model

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Abstract

The congested clique model is a message-passing model of distributed computation where k players communicate with each other over a complete network. Here we consider synchronous protocols in which communication happens in rounds (we allow them to be randomized with public coins). In the unicast communication mode, each player i has her own n-bit input xi and may send k − 1 different b-bit messages through each of her k − 1 communication links in each round. On the other end is the broadcast communication mode, where each player can only broadcast a single message over all her links in each round. The goal of this paper is to complete our Brief Announcement at PODC 2015, where we initiated the study of the space that lies between the two extremes. For that purpose, we parametrize the congested clique model by two values: the range r, which is the maximum number of different messages a player is allowed to send in each round, and the bandwidth b, which is the maximum size of these messages. We show that the space between the unicast and broadcast congested clique models is very rich and interesting. For instance, we show that the round complexity of the pairwise set-disjointness function pwdisj is completely sensitive to the range r. This translates into a Ω(k) gap between the unicast (r = k −1) and the broadcast (r = 1) modes. Moreover, provided that r ≥ 2 and rb/ log r = O(k), the round complexity of pwdisj is Θ(n/k log r). On the other hand, we also prove that the behavior of pwdisj is exceptional: almost every boolean function f has maximal round complexity Θ(n/b). Finally, we prove that min is an upper bound for the gap between the round complexities with parameters (b, r) and parameters (b′, r′) of any boolean function.

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APA

Becker, F., Anta, A. F., Rapaport, I., & Rémila, E. (2016). The effect of range and bandwidth on the round complexity in the congested clique model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9797, pp. 182–193). Springer Verlag. https://doi.org/10.1007/978-3-319-42634-1_15

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