Research on <scp>SIMD</scp> Instruction Sequence Generation Method for Vector <scp>DSP</scp> Processor

ABSTRACT In the field of digital signal processing (DSP), the execution of vector operations depends on the optimization of Single Instruction Multiple Data (SIMD) technology. However, manual SIMD vectorization method is complex to develop, poorly portable, and costly to maintain. Therefore, we propose a method of SIMD instruction sequence generation based on LLVM. This method builds a hierarchical instruction generation framework, combines the characteristics of the target architecture, and uses LLVM automatic vectorization tool to gradually convert the vectorized intermediate representation into the target architecture instruction sequence containing SIMD instructions. Experiments on FT‐M7002 hardware platform show that, compared with the vectorization method of manually calling SIMD built‐in functions, the average execution performance of the instruction sequence generated by this method can be improved by up to 70%.

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Publication Details

Journal
Concurrency and Computation Practice and Experience
Published
2025-12-02
DOI
https://doi.org/10.1002/cpe.70377
Primary Topic
Embedded Systems Design Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Research on SIMD Instruction Sequence Generation Method for Vector DSP Processor

Concurrency and Computation Practice and Experience
Embedded Systems Design Techniques
article

Research on SIMD Instruction Sequence Generation Method for Vector DSP Processor

article en

Abstract

ABSTRACT In the field of digital signal processing (DSP), the execution of vector operations depends on the optimization of Single Instruction Multiple Data (SIMD) technology. However, manual SIMD vectorization method is complex to develop, poorly portable, and costly to maintain. Therefore, we propose a method of SIMD instruction sequence generation based on LLVM. This method builds a hierarchical instruction generation framework, combines the characteristics of the target architecture, and uses LLVM automatic vectorization tool to gradually convert the vectorized intermediate representation into the target architecture instruction sequence containing SIMD instructions. Experiments on FT‐M7002 hardware platform show that, compared with the vectorization method of manually calling SIMD built‐in functions, the average execution performance of the instruction sequence generated by this method can be improved by up to 70%.

Concurrency and Computation Practice and ExperienceVol. 38(1)
Hunan University of Science and Technology (CN)
Natural Science Foundation of Hunan Province
Openalex Percentile: Top 38%
Embedded Systems Design Techniques
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