5 research outputs found

    Parallel Batch-Dynamic Graph Connectivity

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    In this paper, we study batch parallel algorithms for the dynamic connectivity problem, a fundamental problem that has received considerable attention in the sequential setting. The most well known sequential algorithm for dynamic connectivity is the elegant level-set algorithm of Holm, de Lichtenberg and Thorup (HDT), which achieves O(log2n)O(\log^2 n) amortized time per edge insertion or deletion, and O(logn/loglogn)O(\log n / \log\log n) time per query. We design a parallel batch-dynamic connectivity algorithm that is work-efficient with respect to the HDT algorithm for small batch sizes, and is asymptotically faster when the average batch size is sufficiently large. Given a sequence of batched updates, where Δ\Delta is the average batch size of all deletions, our algorithm achieves O(lognlog(1+n/Δ))O(\log n \log(1 + n / \Delta)) expected amortized work per edge insertion and deletion and O(log3n)O(\log^3 n) depth w.h.p. Our algorithm answers a batch of kk connectivity queries in O(klog(1+n/k))O(k \log(1 + n/k)) expected work and O(logn)O(\log n) depth w.h.p. To the best of our knowledge, our algorithm is the first parallel batch-dynamic algorithm for connectivity.Comment: This is the full version of the paper appearing in the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 201
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