Self-Stabilizing Compilation for Parallel Program Abstractions
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Solution Overview
Problem
Existing compiler frameworks lack automated stabilization of program abstractions, leading to inconsistencies that impact the correctness and optimality of optimizations, especially in parallel programming environments, where concurrency complicates the stabilization of seemingly unconnected parts of the code.
Innovation Solution
A computer-implemented method and system for automatic self-stabilizing compilation that generates program abstractions, performs optimization operations, and stabilizes these abstractions using predetermined elementary transformations, maintaining consistency through modes like lazy-invalidate, lazy-update, eager-update, or eager-invalidate stabilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated stabilization of program abstractions is implemented, then the correctness and optimality of optimizations is improved, but the device complexity increases
Solution Approach 1:
The system implements self-service by automatically stabilizing program abstractions without requiring manual intervention from optimization writers. The stabilizer component autonomously detects inconsistencies and performs stabilization operations, eliminating the burden of manual identification and implementation of stabilization logic while ensuring correctness of optimizations.
Solution Approach 2:
The stabilizer acts as an intermediary component between program transformations and program abstractions. It mediates the interaction by monitoring transformations, detecting inconsistencies in abstractions, and performing stabilization operations, thereby isolating the complexity of stabilization logic from both the transformation writers and the core compiler framework.
2Ease of operation
If manual stabilization of program abstractions is performed, then the burden on optimization writers is reduced, but the productivity decreases
Solution Approach 1:
The system applies partial action by performing stabilization only when and where needed, rather than stabilizing all abstractions unconditionally. The stabilizer selectively intervenes based on detected inconsistencies, avoiding unnecessary stabilization operations that would waste time, while still providing automated assistance where required.
Solution Approach 2:
The system implements feedback mechanisms where the stabilizer continuously monitors program abstractions for consistency with current program state. When inconsistencies are detected, the stabilizer performs corrective stabilization operations and verifies their effectiveness, creating a closed-loop system that adapts to the actual needs of the compilation process.
3Reliability
If complete recalculation of program abstractions is performed, then the consistency is improved, but the loss of time increases
Solution Approach 1:
The system segments the stabilization process into targeted operations rather than performing complete recalculation. The stabilizer identifies specific abstractions that require stabilization and applies stabilization operations only to those segments, leaving other abstractions unchanged. This selective approach maintains consistency where needed while avoiding unnecessary time consumption.
Solution Approach 2:
The system performs preliminary actions by maintaining program abstractions in a consistently updated state through incremental stabilization. Rather than waiting for complete inconsistency before acting, the stabilizer performs preliminary stabilization operations that prevent the accumulation of inconsistencies, reducing the need for time-consuming complete recalculation later.
Data Source
AI summary
Disclosed are systems and methods for automatic self-stabilizing compilation of programs. The method includes receiving an input program and generating a plurality of abstractions of the input program using a plurality of analysis operations, by an analysis component (208). Each one of the plurality of abstractions represents a program state. An optimization component (210) performs an optimization operation on one of the plurality of abstractions (316) based on a set of predetermined elementary transformations (408) to modify the program state. A stabilization component (212) performs stabilization of one or more of the plurality of abstractions (316) using the information captured by the set of predetermined elementary transformations in a stabilization mode. The stabilizing includes updating the one or more abstractions (316) to maintain consistency of the abstractions with the program states.


