Towards Relaxed Concurrent Data Structures on Distributed Memory Computer Systems

Abstract

Remote memory access (RMA) technique is a very attractive way for improving efficiency of high-performance computations (HPC) and simplifying parallel program development. However, coming up with efficient concurrent data structures for distributed environments with deep hierarchy, such as computer clusters and data centres, is challenging. We propose a novel approach to design distributed concurrent data structures. The core idea behind the approach is relaxation of the order of executed operations. For example, a relaxed priority queues only requires the elements returned by delete-min operation to be sufficiently close to the minimum. Similarly, in a relaxed queue or stack, the removed elements are close to the first or the last one, respectively. There are multiple evidences that, on most workloads, relaxed data structures outperform data structures with strict semantics and ensure acceptable degrees of operation reordering. In this work we approve our approach on the example of a distributed queue, evaluate its efficiency and compare it with the other implementations of distributed lists.