SOURCE-LINKED INTELLIGENCE
Detecting Soft Errors in Parallel Software with LLM-tuned Instruction Duplication
We propose PaRID (PaRallel Instruction Duplication), a software-directed soft error detection framework that requires only compile-time effort for multithreading parallel programs. PaRID addresses two key challenges: supporting parallel programs with mixed serial and parallel regions and minimizing performance overhead without relying on costly dynamic profiling. It combines parallel-aware code transformation with LLM-tuned performance modeling, guided by eight generalizable findings from an offline characterization study, to enable fast soft error detection in parallel applications. Evaluatio
Read original source ↗ Open in workspace
- recordType
- paper
- region
- Global
Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-17T00:54:35.000Z
- arXiv · Artificial Intelligence · 2026-09-17T00:54:35.000Z
First collected: 2026-09-19T20:26:32.566Z. This is not the publication date.