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HCG: Optimizing Embedded Code Generation of Simulink with SIMD Instruction Synthesis

  • Zhuo Su
  • , Zehong Yu
  • , Dongyan Wang
  • , Yixiao Yang*
  • , Yu Jiang*
  • , Rui Wang
  • , Wanli Chang
  • , Jiaguang Sun
  • *Corresponding author for this work
  • Tsinghua University
  • Renmin University of China
  • Capital Normal University
  • University of York

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Simulink is widely used for the model-driven design of embedded systems. It is able to generate optimized embedded control software code through expression folding, variable reuse, etc. However, for some commonly used computing-sensitive models, such as the models for signal processing applications, the efficiency of the generated code is still limited. In this paper, we propose HCG, an optimized code generator for the Simulink model with SIMD instruction synthesis. It will select the optimal implementations for intensive computing actors based on adaptively pre-calculation of the input scales, and synthesize the appropriate SIMD instructions for batch computing actors based on the iterative dataflow graph mapping. We implemented and evaluated its performance on benchmark Simulink models. Compared to the built-in Simulink Coder and the most recent DFSynth, the code generated by HCG achieves an improvement of 38.9%-92.9% and 41.2%-76.8% in terms of execution time across different architectures and compilers, respectively.

Original languageEnglish
Title of host publicationProceedings of the 59th ACM/IEEE Design Automation Conference, DAC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1033-1038
Number of pages6
ISBN (Electronic)9781450391429
DOIs
StatePublished - 10 Jul 2022
Externally publishedYes
Event59th ACM/IEEE Design Automation Conference, DAC 2022 - San Francisco, United States
Duration: 10 Jul 202214 Jul 2022

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X

Conference

Conference59th ACM/IEEE Design Automation Conference, DAC 2022
Country/TerritoryUnited States
CitySan Francisco
Period10/07/2214/07/22

Keywords

  • code generation
  • model-driven design
  • SIMD instruction
  • simulink

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