JuliaCon 2026

As shown on the Supported platforms Julia page, Julia guarantees “Tier 1” support for common developer platforms such as Windows, macOS, and Linux. This satisfies most users. However, as shown on the Why We Created Julia page, We are greedy: we want more.

We would like to run Julia in offline mobile environments such as airplanes, inside web browsers without long startup delays (TTFX), and even on older ARMv7 (32-bit) Raspberry Pi devices. Due to technical constraints, the official Julia runtime is difficult to use in these settings. In particular, platforms like iOS and iPadOS, where JIT compilation is restricted and app review is strict, are especially challenging.

To address this, we implemented a virtual machine in Rust that accepts and executes a subset of Julia syntax:

https://github.com/AtelierArith/julia-vm-oss

Because Rust is designed for systems programming, it supports many platforms that Julia does not directly target. Since the VM does not rely on JIT compilation, it can be deployed as a native iOS and iPadOS application:

https://apps.apple.com/us/app/subsetjuliavm/id6757257182

Rust can also be compiled to WebAssembly, allowing the VM to be integrated into browser-based applications:

https://terasakisatoshi.github.io/subset_julia/

Actually, the VM itself is largely AI-generated using Claude Code, Codex, and Cursor. Human guidance was used to reference the official Julia implementation and to keep parts written in Julia whenever possible.

We also explored transpiling Julia code into Rust. Initial experiments show that it is possible to generate programs such as Mandelbrot set visualizations and distribute them as standalone binaries. In principle, these binaries can run on any platform supported by Rust.

Compared with approaches that implicitly depend on libjulia, this provides a more portable alternative.

This short talk demonstrates these ideas through live demos.