C codegen considered unnecessary: go directly to binary, do not pass C. Compilation of Julia code for deployment in model-based engineering

TL;DR

This paper demonstrates how Julia's native LLVM-based compilation enables direct deployment of high-level code as binaries for real-time embedded systems, bypassing the need for C code generation.

Contribution

It introduces a novel approach using Julia's LLVM pipeline to compile high-level models directly into architecture-specific binaries for real-time applications.

Findings

Julia can compile to binaries suitable for embedded systems.

The approach simplifies deployment by avoiding C code generation.

Case studies include a Raspberry Pi estimator and a Julia PID library.

Abstract

Since time immemorial an old adage has always seemed to ring true: you cannot use a high-level productive programming language like Python or R for real-time control and embedded-systems programming, you must rewrite your program in C. We present a counterexample to this mantra by demonstrating how recent compiler developments in the Julia programming language allow users of Julia and the equation-based modeling language ModelingToolkit to compile and deploy binaries for real-time model-based estimation and control. Contrary to the approach taken by a majority of modeling and simulation tools, we do not generate C code, and instead demonstrate how we may use the native Julia code-generation pipeline through LLVM to compile architecture-specific binaries from high-level code. This approach avoids many of the restrictions typically placed on high-level languages to enable C-code generation. As case studies, we include a nonlinear state estimator derived from an equation-based model which is compiled into a program that performs state estimation for deployment onto a Raspberry Pi, as well as a PID controller library implemented in Julia and compiled into a shared library callable from a C program.