Brief announcement: 2D-stack - A scalable lock-free stack design that continuously relaxes semantics for better performance
Paper in proceeding, 2018

We briefly describe an efficient lock-free concurrent stack design with tunable and tenable relaxed semantics to allow for better performance. The design is tunable and allow for a continuous monotonic trade of weaker semantics for better throughput performance. Concurrent stacks have an inherent scalability bottleneck due to their single access point for both their operations. Elimination and semantics relaxation have been proposed in the literature to address this problem. Semantics relaxation has the potential to reach monotonically very high throughput by continuously trading relaxation for throughput. Previous solutions could not fully leverage this potential. We suggest a new two dimensional design that can achieve this by exploiting disjoint access parallelism in one dimension and locality in the other within tight accuracy bounds. The behaviour of the algorithm is tightly bound. We compare experimentally to previous work, with respect to throughput and relaxed behaviour observed, on different relaxation and concurrency settings. The experimental evaluation shows that our algorithm significantly outperform all other algorithms in terms of performance, also maintain better accuracy in contrast to other designs with relaxed semantics.










Adones Rakundo

Chalmers, Computer Science and Engineering (Chalmers)

Aras Atalar

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Philippas Tsigas

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Proceedings of the Annual ACM Symposium on Principles of Distributed Computing

978-145035795-1 (ISBN)

37th ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing, PODC 2018
Egham, United Kingdom,

VR Models and Techniques for Energy-Efficient Concurrent Data Access Designs

Swedish Research Council (VR) (VR), 2017-01-01 -- 2020-12-31.

Subject Categories

Communication Systems

Signal Processing

Computer Science



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