@inproceedings{8725, abstract = {The design and implementation of efficient concurrent data structures have seen significant attention. However, most of this work has focused on concurrent data structures providing good \emph{worst-case} guarantees. In real workloads, objects are often accessed at different rates, since access distributions may be non-uniform. Efficient distribution-adaptive data structures are known in the sequential case, e.g. the splay-trees; however, they often are hard to translate efficiently in the concurrent case. In this paper, we investigate distribution-adaptive concurrent data structures and propose a new design called the splay-list. At a high level, the splay-list is similar to a standard skip-list, with the key distinction that the height of each element adapts dynamically to its access rate: popular elements ``move up,'' whereas rarely-accessed elements decrease in height. We show that the splay-list provides order-optimal amortized complexity bounds for a subset of operations while being amenable to efficient concurrent implementation. Experimental results show that the splay-list can leverage distribution-adaptivity to improve on the performance of classic concurrent designs, and can outperform the only previously-known distribution-adaptive design in certain settings.}, author = {Aksenov, Vitaly and Alistarh, Dan-Adrian and Drozdova, Alexandra and Mohtashami, Amirkeivan}, booktitle = {34th International Symposium on Distributed Computing}, isbn = {9783959771689}, issn = {1868-8969}, location = {Freiburg, Germany}, pages = {3:1--3:18}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik}, title = {{The splay-list: A distribution-adaptive concurrent skip-list}}, doi = {10.4230/LIPIcs.DISC.2020.3}, volume = {179}, year = {2020}, }