Adjusted Objects: An Efficient and Principled Approach to Scalable Programming (Extended Version)

2025-04-28

AI Summary

Redundant generic shared-object APIs in parallel programs incur substantial performance overhead. This paper introduces the “Tuned Objects” paradigm: domain-specific shared data structures (e.g., queues, maps, counters) meticulously streamlined and optimized for particular concurrency patterns. We present the first systematic formalization of this paradigm, establish a scalability analysis framework grounded in indistinguishability graphs, and distill practical, customizable design principles. We implement DEGO, a Java library embodying these principles, and evaluate it via microbenchmarks and the Retwis social-network workload. Microbenchmarks show up to 100× speedup over JDK standard objects; application-level evaluation demonstrates up to 1.7× higher single-machine throughput. Our core contributions unify formal modeling—via indistinguishability-based scalability analysis—with a principled design methodology and empirical validation across both micro- and macro-benchmarks.

Technology Category

• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

Parallel programs require software support to coordinate access to shared data. For this purpose, modern programming languages provide strongly-consistent shared objects. To account for their many usages, these objects offer a large API.However, in practice, each program calls only a tiny fraction of the interface. Leveraging such an observation, we propose to tailor a shared object for a specific usage. We call this principle adjusted objects. Adjusted objects already exist in the wild. This paper provides their first systematic study. We explain how everyday programmers already adjust common shared objects (such as queues, maps, and counters) for better performance. We present the formal foundations of adjusted objects using a new tool to characterize scalability, the indistinguishability graph. Leveraging this study, we introduce a library named DEGO to inject adjusted objects in a Java program. In micro-benchmarks, objects from the DEGO library improve the performance of standard JDK shared objects by up to two orders of magnitude. We also evaluate DEGO with a Retwis-like benchmark modeled after a social network application. On a modern server-class machine, DEGO boosts by up to 1.7x the performance of the benchmark.

Problem

• Tailoring shared objects for specific program usage
• Improving performance via adjusted shared objects
• Systematic study and library for scalable programming

Innovation

• Tailors shared objects for specific usage
• Uses indistinguishability graph for scalability
• Introduces DEGO library for Java performance