KMat

KMat is an open-source matrix library designed for numerical computing in Kotlin and the JVM ecosystem. It provides a range of matrix types and operations intended for scientific, engineering, and data analysis tasks, with an emphasis on a Kotlin-friendly API and multiplatform compatibility.

KMat offers dense and sparse matrix representations, along with a core set of linear algebra routines. Users can perform standard arithmetic (addition, subtraction, multiplication), transpose operations, and matrix decompositions such as LU, Cholesky, eigenvalue, and singular value decompositions. The library also includes solvers for linear systems, factorization-based methods, and support for common matrix‑vector operations. Its design aims to be idiomatic to Kotlin, leveraging operator overloading and concise syntax to improve readability and expressiveness.

The project emphasizes interoperability with Java’s numeric ecosystem. It can utilize native backends or optimized libraries where available, such as BLAS/LAPACK bindings, while also providing pure Kotlin fallbacks for environments without native libraries. KMat is intended to work across Kotlin Multiplatform targets, including JVM, Android, and JavaScript, with ongoing efforts toward broader platform support and consistent behavior across backends.

Usage typically involves creating matrix objects from Kotlin arrays or streams, selecting a storage format (dense or sparse), and invoking standard operations or decompositions. The API is designed to be approachable for developers familiar with linear algebra, while remaining flexible enough to integrate into larger data processing workflows or scientific simulations.

KMat was released under an open-source license and is maintained by a community of contributors. It competes with other numerical libraries in the Kotlin and Java ecosystems, offering a Kotlin-first alternative for matrix computations.

See also: linear algebra, matrix library, Kotlin Multiplatform.