Is it possible to make self-adjusting data structures concurrent?

A Google TechTalk, presented by Vitaly Aksenov, 2024-06-25
Google Algorithms Seminar. ABSTRACT: In this talk, we cover several aspects of self-adjusting data structures. These data structures answer more frequent queries faster. The most famous example is the SplayTree, which rotates the accessed node to the root, leading to a lower depth for frequently accessed nodes. Obviously, such an approach is averse to concurrency, as there is a very high contention on the root. The first concurrent self-adjusting data structure is a binary tree CBTree, which was presented in 2012, but like the concurrent AVL tree it is based on, it does not have much scalability due to the hand-over-hand validation traversals.
We decided to look at the problem from a different direction. As was clear a long time ago, a SkipList is much easier to make concurrent than any balanced binary tree. Thus, we designed a self-adjusting concurrent SkipList named Splay-List and proved its complexity. Then, we found work on a concurrent Interpolation Search Tree (IST) that is built on efficient lazy rebuilding. Thus, we discuss how to make self-adjusting multi-way data structures quite easily using lazy rebuilding, with examples of B-tree and IST, providing a possibility for efficient concurrent implementations.
This talk almost does not require any prior knowledge and relies on the interest in data structures by the listeners.
ABOUT THE SPEAKER: Vitaly Aksenov is currently an Assistant Professor at City, University of London. His research focuses on self-adjusting systems and practice and theory of parallel and concurrent data structures.
Before joining City, University of London, Vitaly was an Assistant Professor at ITMO University for a while and prior to that, he was a post-doc in IST Austria under the guidance of professor Dan Alistarh. He received his PhD from Paris 7 Diderot and ITMO University under the guidance of professor Petr Kuznetsov.