pLiner: isolating lines of floating-point code for compiler-induced variability
Hui Guo, Ignacio Laguna, Cindy Rubio-González
摘要
Scientific applications are often impacted by numerical inconsistencies when using different compilers or when a compiler is used with different optimization levels; such inconsistencies hinder reproducibility and can be hard to diagnose. We present PLINER, a tool to automatically pinpoint code lines that trigger compiler-induced variability. PLINER uses a novel approach to enhance floating-point precision at different levels of code granularity, and performs a guided search to identify locations affected by numerical inconsistencies. We demonstrate PLINER on a real-world numerical inconsistency that required weeks to diagnose, which PLINER isolates in minutes. We also evaluate PLiNER on 100 synthetic programs, and the NAS Parallel Benchmarks (NPB). On the synthetic programs, PLiNER detects the affected lines of code 87% of the time while the stateof-the-art approach only detects the affected lines 6% of the time. Furthermore, PLINER successfully isolates all numerical inconsistencies found in the NPB.
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- Finding Inputs that Trigger Floating-Point Exceptions in GPUs via Bayesian OptimizationIgnacio Laguna, Ganesh GopalakrishnanSC 2022 · 被引用 10 次
- Predicting Performance and Accuracy of Mixed-Precision Programs for Precision TuningYutong Wang, Cindy Rubio-GonzálezICSE 2024 · 被引用 7 次
- Revealing Floating-Point Accumulation Orders in Software/Hardware ImplementationsPeichen Xie, Yanjie Gao, Yang Wang, Jilong XueUSENIX ATC 2025 · 被引用 6 次
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