基于区域划分的跨基本块SLP向量化技术

doi:10.11896/jsjkx.241100130

Computer Science ›› 2025, Vol. 52 ›› Issue (9): 186-194.doi: 10.11896/jsjkx.241100130

• High Performance Computing • Previous Articles Next Articles

SLP Vectorization Across Basic Blocks Based on Region Partitioning

HAN Lin^1,2, DING Yongqiang¹, CUI Pingfei¹, LIU Haohao², LI Haoran², CHEN Mengyao²

1 College of Cyber Security,Zhongyuan University of Technology,Zhengzhou 451191,China
2 National Supercomputing Center in Zhengzhou,Zhengzhou 450001,China

Received:2024-11-25 Revised:2025-04-15 Online:2025-09-15 Published:2025-09-11
About author:HAN Lin,born in 1978,professor,doctoral supervisor,is a member of CCF(No.16416M).His main research interests include high-performance computing,advanced compilation,program optimization and home-grown autonomous control.
CUI Pingfei,born in 1975,associate professor,master supervisor.His main research interests include domestic so-vereign control,software reverse engineering and code security analysis.
Supported by:
2024 Henan Provincial Science and Technology Tackling Project(242102211094) and 2022 Major Science and Technology Programs in Henan Province 17(221100210600).

Abstract

Abstract: Automatic vectorization is a key technique in mainstream compilers for uncovering data-level parallelism and enhancing program performance.Traditional SLP vectorization struggles with cross-basic-block statement vectorization,particularly when consecutive vectorizable instructions are split by basic block boundaries,limiting its ability to detect potential vectorization opportunities.To address this,this paper proposes a region-based cross-basic-block SLP vectorization method that extends the analysis scope to multiple basic blocks within dominance relations,effectively breaking basic block boundaries and uncovering more vectori-zation opportunities.Implemented in the GCC 10.3.0 compiler,the proposed method is evaluated using relevant program segments from the SPEC CPU2006 benchmark.Experimental results demonstrate that the proposed method achieves up to a 12% speedup in SPEC CPU2006,an average speedup of 8% for related test programs,and a 3% average speedup in the Polybench benchmark compared to traditional SLP methods,validating its effectiveness.This work provides a technical reference for improving SLP vectorization efficiency in GCC compilers.

Key words: Compilation optimization, Automatic vectorization, SLP, Across basic blocks, Region partitioning

CLC Number:

TP314

HAN Lin, DING Yongqiang, CUI Pingfei, LIU Haohao, LI Haoran, CHEN Mengyao. SLP Vectorization Across Basic Blocks Based on Region Partitioning[J].Computer Science, 2025, 52(9): 186-194.

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