We propose algorithms to perform operations concurrently on treaps in a shared memory multi-core environment. Concurrent treaps hold the advantage of using nodes’ priority for maintaining the height of the treaps. To achieve synchronization, concurrent treaps make use of fine-grained locking mechanism along with logical ordering and physical ordering of nodes’ keys. We initially study the throughput and performance-per-Watt (PPW) of our concurrent treap implementation and observe that it scales well, and performs better than the state-of-the-art implementations. We further continue studies to understand the impact of different locking objects on both throughput and PPW. Our experiments show that a concurrent treap implementation that uses AtomicInteger as the locking object provides better throughput and PPW, at the same time uses a low memory footprint. As part of the application study, we consider concurrent interval trees by choosing different underlying concurrent search tree implementations as the base. We observe that the concurrent interval tree implementation that uses concurrent treap as an underlying data structure provides better throughput.

中文翻译：

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并发陷阱和锁定对象的影响

我们提出了在共享内存多核环境中对 treap 并发执行操作的算法。并发 treaps 的优点是使用节点的优先级来维护 treaps 的高度。为了实现同步，并发陷阱利用细粒度锁定机制以及节点键的逻辑排序和物理排序。我们最初研究了并发 treap 实现的吞吐量和每瓦性能 (PPW)，并观察到它具有良好的扩展性，并且比最先进的实现性能更好。我们进一步研究以了解不同锁定对象对吞吐量和 PPW 的影响。我们的实验表明，使用 AtomicInteger 作为锁定对象的并发 treap 实现提供了更好的吞吐量和 PPW，同时使用低内存占用。作为应用研究的一部分，我们通过选择不同的底层并发搜索树实现作为基础来考虑并发间隔树。我们观察到，使用并发 treap 作为底层数据结构的并发间隔树实现提供了更好的吞吐量。