A high performance WebAssembly interpreter written in C.

∼ 8x faster than other known wasm interpreters
∼ 4-5x slower than state of the art wasm JIT engines
∼ 12x slower than native execution
_{* Based on CoreMark 1.0 benchmark. Your mileage may vary.}

Here's an online demo and a small getting started guide:

wasm3 passes the WebAssembly spec testsuite and is able to run many WASI apps.

Minimum useful system requirements: ~64Kb for code and ~10Kb RAM

wasm3 runs on a wide range of architectures (x86, x86_64, ARM, RISC-V, PowerPC, MIPS, Xtensa, ARC32, ...) and platforms:

• Linux, Windows, OS X, FreeBSD
• Android, iOS
• OpenWRT-enabled routers
• Raspberry Pi, Orange Pi and other SBCs
• MCUs: Arduino, ESP8266, ESP32, Particle, ... see full list
• Browsers... yes, using WebAssembly itself!
• wasm3 can execute wasm3 (self-hosting)

☑ Sign-extension operators
☑ Non-trapping float-to-int conversions
☐ Bulk memory operations
☐ Multi-value
☐ Import/Export of Mutable Globals
☐ Tail call
☐ Fixed-width SIMD

Please follow the installation instructions.
Wasm3 can be used as a library for:

Python3 │ C/C++ │ GoLang │ Rust │ Arduino, PlatformIO, Particle

Why use a "slow interpreter" versus a "fast JIT"?

In many situations, speed is not the main concern. Runtime executable size, code density, memory usage, startup latency can be all improved with the interpreter approach. Portability and security are much easier to achieve and maintain. Additionally, development impedance is much lower. A simple library like Wasm3 is easy to compile and integrate into an existing project. (Wasm3 builds in a just few seconds). Finally, on some platforms (i.e. iOS and WebAssembly itself) you can't generate executable code pages in runtime, so JIT is unavailable.

Why would you want to run WASM on microcontrollers?

Wasm3 started as a research project and remains so by many means. Evaluating the engine in different environments is part of the research. Given that we have Lua, JS, Python, Lisp, ... running on MCUs, WebAssembly is actually a promising alternative. It provides toolchain decoupling as well as a completely sandboxed, well-defined, predictable environment. Among practical use cases we can list edge computing, scripting, running IoT rules, smart contracts, etc.

Demos
Installation instructions
Build and Development instructions
Supported Hardware
Testing & Fuzzing
Performance
Interpreter Architecture
Logging

This project is released under The MIT License (MIT)