MILJS : Brand New JavaScript Libraries for Matrix Calculation and Machine Learning

TL;DR

MILJS offers a set of high-performance, easy-to-use JavaScript libraries for matrix calculations, machine learning, and visualization, enabling efficient ML development directly in web browsers.

Contribution

Introduction of Sushi, a fast matrix calculation library, and Tempura, a machine learning library, optimized for JavaScript with superior performance and usability.

Findings

Sushi's matrix multiplication is 177 times faster than existing JavaScript libraries.

The libraries are platform-independent, scalable, and easy to use in web browsers.

Performance benchmarks show significant speed improvements over prior JavaScript ML tools.

Abstract

MILJS is a collection of state-of-the-art, platform-independent, scalable, fast JavaScript libraries for matrix calculation and machine learning. Our core library offering a matrix calculation is called Sushi, which exhibits far better performance than any other leading machine learning libraries written in JavaScript. Especially, our matrix multiplication is 177 times faster than the fastest JavaScript benchmark. Based on Sushi, a machine learning library called Tempura is provided, which supports various algorithms widely used in machine learning research. We also provide Soba as a visualization library. The implementations of our libraries are clearly written, properly documented and thus can are easy to get started with, as long as there is a web browser. These libraries are available from http://mil-tokyo.github.io/ under the MIT license.