  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.
