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This paper provides three nearly-optimal algorithms for scheduling $t$ jobs in the $mathsf{CLIQUE}$ model. First, we present a deterministic scheduling algorithm that runs in $O(mathsf{GlobalCongestion} + mathsf{dilation})$ rounds for jobs that are sufficiently efficient in terms of their memory. The $mathsf{dilation}$ is the maximum round complexity of any of the given jobs, and the $mathsf{GlobalCongestion}$ is the total number of messages in all jobs divided by the per-round bandwidth of $n^2$ of the $mathsf{CLIQUE}$ model. Both are inherent lower bounds for any scheduling algorithm. Then, we present a randomized scheduling algorithm which runs $t$ jobs in $O(mathsf{GlobalCongestion} + mathsf{dilation}cdotlog{n}+t)$ rounds and only requires that inputs and outputs do not exceed $O(nlog n)$ bits per node, which is met by, e.g., almost all graph problems. Lastly, we adjust the emph{random-delay-based} scheduling algorithm [Ghaffari, PODC15] from the $mathsf{CLIQUE}$ model and obtain an algorithm that schedules any $t$ jobs in $O(t / n + mathsf{LocalCongestion} + mathsf{dilation}cdotlog{n})$ rounds, where the $mathsf{LocalCongestion}$ relates to the congestion at a single node of the $mathsf{CLIQUE}$. We compare this algorithm to the previous approaches and show their benefit. We schedule the set of jobs on-the-fly, without a priori knowledge of its parameters or the communication patterns of the jobs. In light of the inherent lower bounds, all of our algorithms are nearly-optimal. We exemplify the power of our algorithms by analyzing the message complexity of the state-of-the-art MIS protocol [Ghaffari, Gouleakis, Konrad, Mitrovic and Rubinfeld, PODC18], and we show that we can solve $t$ instances of MIS in $O(t + loglogDeltalog{n})$ rounds, that is, in $O(1)$ amortized time, for $tgeq loglogDeltalog{n}$.
In this work, we use algebraic methods for studying distance computation and subgraph detection tasks in the congested clique model. Specifically, we adapt parallel matrix multiplication implementations to the congested clique, obtaining an $O(n^{1-2
We design fast deterministic algorithms for distance computation in the congested clique model. Our key contributions include: -- A $(2+epsilon)$-approximation for all-pairs shortest paths in $O(log^2{n} / epsilon)$ rounds on unweighted undirected
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While algebrisation constitutes a powerful technique in the design and analysis of centralised algorithms, to date there have been hardly any applications of algebraic techniques in the context of distributed graph algorithms. This work is a case stu
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