The sequential semantics of many concurrent data structures, such as stacks and queues, inevitably lead to memory contention in parallel environments, thus limiting scalability. Semantic relaxation has the potential to address this issue, increasing the parallelism at the expense of weakened semantics. Although prior research has shown that improved performance can be attained by relaxing concurrent data structure semantics, there is no one-size-fits-all relaxation that adequately addresses the varying needs of dynamic executions. In this paper, we first introduce the concept of elastic relaxation and consequently present the Lateral structure, which is an algorithmic component capable of supporting the design of elastically relaxed concurrent data structures. Using the Lateral , we design novel elastically relaxed, lock-free queues and stacks capable of reconfiguring relaxation during run time. We establish linearizability and define upper bounds for relaxation errors in our designs. Experimental evaluations show that our elastic designs hold up against state-of-the-art statically relaxed designs, while also swiftly managing trade-offs between relaxation and operational latency. We also outline how to use the Lateral to design elastically relaxed lock-free counters and deques.

翻译：许多并发数据结构（如栈和队列）的顺序语义在多核并行环境中不可避免地会导致内存竞争，从而限制了可扩展性。语义松弛通过削弱语义来增加并行性，为解决此问题提供了潜力。尽管已有研究表明放松并发数据结构的语义可提升性能，但不存在一种通用的放松方案能充分适应动态执行中的多变需求。本文首先引入弹性松弛的概念，进而提出Lateral结构——一种支持弹性松弛并发数据结构设计的算法组件。利用Lateral，我们设计了新型的弹性松弛无锁队列与栈，它们能在运行时动态调整松弛程度。我们建立了这些设计的线性化性质，并定义了松弛误差的上界。实验评估表明，我们的弹性设计与最先进的静态松弛设计相比表现优异，同时能快速权衡松弛程度与操作延迟之间的关系。此外，我们还概述了如何利用Lateral设计弹性松弛的无锁计数器和双端队列。