Open-source runtime that executes MATLAB syntax on CPU and GPU automatically, with cross-platform hardware support and no vendor lock-in.
RunMat is an open-source runtime that executes MATLAB-style syntax, automatically accelerating numerical computations on both CPU and GPU hardware. It solves the problem of proprietary licensing and vendor lock-in by providing a cross-platform, high-performance alternative for array-heavy math workloads. The system intelligently fuses operations and chooses the optimal hardware (CPU or GPU) without requiring manual kernel code or device management.
Researchers, engineers, and students who work with MATLAB syntax and need faster performance on their existing hardware, especially those dealing with imaging/geospatial processing, quantitative finance simulations, signal processing, and large-scale numerical analysis.
Developers choose RunMat because it offers MATLAB language compatibility without license fees, automatic GPU acceleration across multiple hardware vendors, and a modern architecture built in Rust for safety and performance. Its unique selling point is the fusion engine that automatically optimizes and offloads work to GPU, eliminating the need for manual kernel programming or device flags.
Open-source runtime for math. Write MATLAB syntax, run on CPU + GPU across platforms (Mac/Win/Linux/Web).
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Runs existing .m files with minimal changes, supporting familiar arrays and control flow, which simplifies migration from proprietary MATLAB environments.
Intelligently fuses operations and routes work to GPU using wgpu/WebGPU across Metal, DirectX 12, Vulkan, and WebGPU, eliminating manual kernel coding for many dense numerical workloads.
Benchmarks show up to 131x faster than NumPy and 7x faster than PyTorch on Monte Carlo simulations, with tiered CPU execution and fusion optimizations.
Available as CLI, NPM package for web embedding, and WebAssembly runtime, enabling deployment from desktop to browser without server dependency.
At version 0.3, the project warns of 'a few rough edges,' making it risky for mission-critical applications until more mature releases are available.
With 300+ built-in functions, it covers core MATLAB but lacks the extensive toolboxes and specialized features of the full proprietary suite, and the package manager is still in design.
Requires manual installation of OpenBLAS for optimal CPU performance, adding an extra step compared to more plug-and-play alternatives like Octave or Python environments.
Advanced plot types like box plots and violin plots are still in progress, limiting visualization capabilities for statistical and scientific applications.
RunMat is an open-source alternative to the following products: