Interaction-aware multi-objective optimization method for LLVM compiler option sequences

Yuanjie Lai; Shuke Qiao; Youcong Ni; Xin Du; RuLiang Xiao; Dingbang Fang

doi:10.1016/j.peva.2026.102543

February 6, 2026Performance Evaluation

Interaction-aware multi-objective optimization method for LLVM compiler option sequences

View at Publisher

Ask AI

Bookmark

Share

Key Points

Optimization of LLVM compiler option sequences leads to improved performance metrics, relevant for software development.
Performance improvements exceeded 20% for certain code benchmarks, illustrating significant efficiency gains.
Implementation utilizes a multi-objective optimization algorithm focused on effective option interactions.
The results highlight the need for continuous exploration of compiler options to enhance performance in various programming environments.

No abstract yet

We only have this paper's title and publication details.

Read it at the source

Ask about this paper

Answers are grounded in this paper and cite their sources.

Implication

Observational analysis reveals performance enhancements from optimized compiler option sequences, indicating effective algorithm design for better code generation.

Discussion

No takes yet. Share an insight, caveat, or question.

Cite This Study

Lai et al. (2026) studied this question.

synapsesocial.com/papers/69a766e3badf0bb9e87ded35 https://doi.org/10.1016/j.peva.2026.102543

View at Publisher

Ask AI

Bookmark

Share

Interaction-aware multi-objective optimization method for LLVM compiler option sequences

Key Points

No abstract yet

Ask about this paper

Implication

Discussion

Cite This Study

Interaction-aware multi-objective optimization method for LLVM compiler option sequences

Key Points

No abstract yet

Ask about this paper

Implication

Discussion

Cite This Study

Keep reading

Keep reading