Abstract
We present the CBTree, a new counting-based self-adjusting binary search tree that, like splay trees, moves more frequently accessed nodes closer to the root. After m operations on n items, c of which access some item v, an operation on v traverses a path of length \(\mathcal{O}(\log\dfrac{m}{c})\) while performing few if any rotations. In contrast to the traditional self-adjusting splay tree in which each accessed item is moved to the root through a sequence of tree rotations, the CBTree performs rotations infrequently (an amortized subconstant o(1) per operation if m ≫ n), mostly at the bottom of the tree. As a result, the CBTree scales with the amount of concurrency. We adapt the CBTree to a multicore setting and show experimentally that it improves performance compared to existing concurrent search trees on non-uniform access sequences derived from real workloads.
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Afek, Y., Kaplan, H., Korenfeld, B., Morrison, A., Tarjan, R.E. (2012). CBTree: A Practical Concurrent Self-Adjusting Search Tree. In: Aguilera, M.K. (eds) Distributed Computing. DISC 2012. Lecture Notes in Computer Science, vol 7611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33651-5_1
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