PHCG: Optimizing Simulink Code Generation for Embedded System With SIMD Instructions

• Published in: IEEE transactions on computer-aided design of integrated circuits and systems Vol. 42; no. 4; pp. 1072 - 1084
• Main Authors: Su, Zhuo, Wang, Dongyan, Yu, Zehong, Yang, Yixiao, Jiang, Yu, Wang, Rui, Chang, Wanli, Li, Wen, Cui, Aiguo, Sun, Jiaguang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Code generation; Codes; Computation; Computational modeling; Computer architecture; Data models; Embedded systems; Graph theory; Integrated circuit modeling; Iterative methods; Merging; model-driven design; Optimization; SIMD (computers); Simulink; single-instruction > multiple-data (SIMD) instruction; Software packages
• ISSN: 0278-0070; 1937-4151
• DOI: 10.1109/TCAD.2022.3197504

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 article, we propose PHCG, an optimized code generator for the Simulink model with single-instruction-multiple-data (SIMD) instruction synthesis. It will select the optimal implementations for intensive computing actors based on adaptively precalculation of the input scales, and synthesize the appropriate SIMD instructions for batch computing actors based on the iterative dataflow graph mapping. In addition, actors of the same type that can be executed in parallel can be combined into batch computing actors as much as possible by merging isomorphic subgraphs. 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 PHCG achieves an improvement of 38.9%-92.9% and 41.2%-76.8% in terms of execution time across different architectures and compilers, respectively.