Peepco: Batch-Based Consistency Optimization
Author(s)
Kuraj, Ivan
Feser, John
Polikarpova, Nadia
Solar-Lezama, Armando
Date Issued
April 9, 2025
Journal
Proceedings of the ACM on Programming Languages
Publisher
ACM
Citation
Ivan Kuraj, John Feser, Nadia Polikarpova, and Armando Solar-Lezama. 2025. Peepco: Batch-Based Consistency Optimization. Proc. ACM Program. Lang. 9, OOPSLA1, Article 119 (April 2025), 29 pages.
Version
Final published version
Abstract
We present batch-based consistency, a new approach for consistency optimization that allows programmers to specialize consistency with application-level integrity properties. We implement the approach with a two-step process: we statically infer optimal consistency requirements for executions of bounded sets of operations, and then, use the inferred requirements to parameterize a new distributed protocol to relax operation reordering at run time when it is safe to do so. Our approach supports standard notions of consistency. We implement batch-based consistency in Peepco, demonstrate its expressiveness for partial data replication, and examine Peepco’s run-time performance impact in different settings.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3720513
