Work

Peepco: Batch-Based Consistency Optimization

Year: 2025

Type: article

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.

Source: Proceedings of the ACM on Programming Languages

DOI: 10.1145/3720513

Authors: Ivan Kuraj, John Feser, Nadia Polikarpova, Armando Solar-Lezama

Institutions: Massachusetts Institute of Technology, University of California San Diego

Language: English

Topic: Distributed systems and fault tolerance

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funder: National Science Foundation

Awards: Expeditions: Collaborative Research: Understanding the World Through Code, PPoSS: LARGE: Intel: Combining Learning and Formal Verification for Scalable Machine Programming (ScaMP)