numerike

Numerike is a conceptual software stack for high-precision numerical computation and data analysis. It brings together numeric engines, symbolic-numeric workflows, and scalable pipelines to support reproducible computation in research, engineering, and finance.

At its core lies the Numerike Core engine, which coordinates arithmetic backends, task scheduling, and memory management. It supports multiple numeric representations, including arbitrary-precision floats, fixed-point, and symbolic expressions, with mechanisms to switch between backends as needed. It targets heterogeneous hardware, providing backends for CPUs, GPUs, and accelerators, and offers both eager and lazy evaluation models to optimize performance. Automatic differentiation is integrated for optimization and machine learning workflows.

Numerike includes NQL, the Numerike Query Language, a functional language designed to express numerical transformations, matrix algebra, and data piping. It provides bindings for Python, C++, and Julia, enabling integration with existing tools. The data model centers on tensors, matrices, and scalars, with support for unit-aware arithmetic, shape inference, and broadcasting rules. The framework emphasizes numerical stability and reproducibility, with features for robust error handling and deterministic random-number generation.

Applications span scientific simulation, computational finance, engineering optimization, and education. Use cases include high-precision simulations, sensitivity analysis, uncertainty quantification, and curricula that teach numerical methods with live reproducible notebooks.

Status and reception: Numerike is described in theoretical and experimental contexts, with several open-source prototypes and reference implementations. It remains a niche concept rather than a standard in industry, valued for its emphasis on precision, portability, and interoperability across languages and hardware.