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20242026
most citedA Method for Efficient Heterogeneous Parallel Compilation: A Cryptography Case Study

3 citations · 3 across the 14 of their papers we have counts for

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6 papers · 1 filter

cs.SE2026

A Case for Agentic Tuning: From Documentation to Action in PostgreSQL

Hongyu Lin, Mingyu Li, Weichen Zhang +4

Documentation has long guided computer system tuning by distilling expert knowledge into per-parameter recommendations. Yet such guides capture only what experts conclude, discardi…

cs.SE2025

VecIntrinBench: Benchmarking Cross-Architecture Intrinsic Code Migration for RISC-V Vector

Liutong Han, Chu Kang, Mingjie Xing +1

Intrinsic functions are specialized functions provided by the compiler that efficiently operate on architecture-specific hardware, allowing programmers to write optimized code in a…

cs.SE2025

A Hybrid, Knowledge-Guided Evolutionary Framework for Personalized Compiler Auto-Tuning

Haolin Pan, Hongbin Zhang, Mingjie Xing +1

Compiler pass auto-tuning is critical for enhancing software performance, yet finding the optimal pass sequence for a specific program is an NP-hard problem. Traditional, general-p…

cs.SE2025

Synergy-Guided Compiler Auto-Tuning of Nested LLVM Pass Pipelines

Haolin Pan, Jinyuan Dong, Mingjie Xing +1

Compiler optimization relies on sequences of passes to improve program performance. Selecting and ordering these passes automatically, known as compiler auto-tuning, is challenging…

cs.SE2025

GRACE: Cluster-Specific Sequence Reuse for Compiler Auto-Tuning

Haolin Pan, Chao Zha, Jinyuan Dong +2

Compiler auto-tuning aims to improve optimization quality beyond fixed compiler heuristics, but existing approaches often face a trade-off between effectiveness and deployability.…

cs.SE2025

IntrinTrans: LLM-based Intrinsic Code Translator for RISC-V Vector

Liutong Han, Zhiyuan Tan, Hongbin Zhang +4

The use of intrinsic functions to leverage hardware-specific capabilities is a crucial approach for optimizing library performance. Many mainstream libraries implement a large numb…