Supxy

Supxy is an open-source software library designed to streamline high-performance numerical computing and data manipulation across platforms. It provides a modular runtime and a set of data structures that enable scientists and developers to implement algorithms that scale from desktop workstations to computing clusters. The library emphasizes interoperability, offering bindings for Python, C++, and JavaScript, with support for CPU and accelerator backends.

Architecturally, Supxy comprises a core execution engine, reusable components such as data containers and parallel schedulers, and a plugin system for custom backends and extensions. The core emphasizes memory efficiency and predictable performance, while optional GPU acceleration via CUDA and ROCm speeds up vector and matrix operations. The project includes a well-documented API, comprehensive tests, and tooling to assist integration with existing workflows.

Supxy emerged from an open-source research community that sought a unified interface for heterogeneous computing workflows. It matured through broader community contributions and is governed by a lightweight foundation that coordinates releases, benchmarks, and compatibility guidelines. The project prioritizes portability, supporting major operating systems and language runtimes, as well as compatibility with common data formats and tools used in scientific computing.

In practice, Supxy is used for numerical simulations, data preprocessing for machine learning, data transformation pipelines, and exploratory analysis. It is regarded as a flexible option for teams seeking to compose specialized data workflows without relying on a single monolithic framework. Related topics include data science software, numerical libraries, and open-source licenses.