Enhancing Compiler Optimization Efficiency through Grammatical Decompositions of Control-Flow Graphs
Xuran Cai

TL;DR
This paper introduces SPL decomposition, a novel graph-based framework that improves compiler optimization efficiency by addressing sparsity and computational costs in control-flow graphs, leading to better register allocation, redundancy elimination, and instruction placement.
Contribution
The thesis presents SPL decomposition as a new method for optimizing compiler tasks, providing optimal solutions for complex problems like register allocation and redundancy elimination.
Findings
Enhanced register allocation performance across benchmarks
Effective redundancy elimination with LOSPRE optimization
Reduced latency through optimized bank selection instructions
Abstract
This thesis addresses the complexities of compiler optimizations, such as register allocation and Lifetime-optimal Speculative Partial Redundancy Elimination (LOSPRE), which are often handled using tree decomposition algorithms. However, these methods frequently overlook important sparsity aspects of Control Flow Graphs (CFGs) and result in high computational costs. We introduce the SPL (Series-Parallel-Loop) decomposition, a novel framework that offers optimal solutions to these challenges. A key contribution is the formulation of a general solution for Partial Constraint Satisfaction Problems (PCSPs) within graph structures, applied to three optimization problems. First, SPL decomposition enhances register allocation by accurately modeling variable interference graphs, leading to efficient register assignments and improved performance across benchmarks. Second, it optimizes LOSPRE by…
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Taxonomy
TopicsParallel Computing and Optimization Techniques · Constraint Satisfaction and Optimization · Formal Methods in Verification
