Series-parallel-loop decompositions of control-flow graphs

2026-02-01

Journal of systems architecture

AI Summary

This work addresses the limitations of existing compiler optimization techniques that rely on graph parameters such as treewidth, which often fail to accurately capture the intrinsic structural constraints of control flow graphs (CFGs) derived from structured programs. To overcome this, the paper introduces a syntax-driven Series-Parallel-Loop (SPL) decomposition framework that aligns graph decomposition with the syntactic structure of the source program, thereby precisely characterizing structured CFGs. Leveraging this decomposition, the authors design specialized dynamic programming algorithms tailored for register allocation and Lazy On-the-Side Partial Redundancy Elimination (LOSPRE). Experimental results demonstrate that the proposed approach significantly outperforms state-of-the-art methods on both tasks, confirming the efficacy and performance advantages of CFG-specific decomposition guided by program syntax.

Technology Category

• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Combinatorial Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies

Problem

• Control-flow graphs
• Structured programs
• Graph sparsity
• Treewidth
• Program analysis

Innovation

• Series-Parallel-Loop Decomposition
• Control-Flow Graphs
• Structured Programs
• Grammar-Based Decomposition
• Compiler Optimization