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We start by summarizing the recently proposed implementation of the first non-blocking concurrent interpolation search tree (C-IST) data structure. We then analyze the individual operations of the C-IST, and show that they are correct and linearizable. We furthermore show that lookup (and several other non-destructive operations) are wait-free, and that the insert and delete operations are lock-free. We continue by showing that the C-IST has the following properties. For arbitrary key distributions, this data structure ensures worst-case $O(log n + p)$ amortized time for search, insertion and deletion traversals. When the input key distributions are smooth, lookups run in expected $O(log log n + p)$ time, and insertion and deletion run in expected amortized $O(log log n + p)$ time, where $p$ is a bound on the number of threads. Finally, we present an extended experimental evaluation of the non-blocking IST performance.
This paper presents the first implementation of a search tree data structure in an asynchronous shared-memory system that provides a wait-free algorithm for executing range queries on the tree, in addition to non-blocking algorithms for Insert, Delet
We consider the design of adaptive data structures for searching elements of a tree-structured space. We use a natural generalization of the rotation-based online binary search tree model in which the underlying search space is the set of vertices of
Recently Avis and Jordan have demonstrated the efficiency of a simple technique called budgeting for the parallelization of a number of tree search algorithms. The idea is to limit the amount of work that a processor performs before it terminates its
We describe a general technique for obtaining provably correct, non-blocking implementations of a large class of tree data structures where pointers are directed from parents to children. Updates are permitted to modify any contiguous portion of the
We show the $O(log n)$ time extract minimum function of efficient priority queues can be generalized to the extraction of the $k$ smallest elements in $O(k log(n/k))$ time, where we define $log(x)$ as $max(log_2(x), 1)$. We first show heap-ordered tr