sysfloatinfomax

Sysfloatinfomax, short for System Float Information Maximization, is a theoretical framework and set of algorithms designed to maximize the information content preserved in floating-point computations within digital systems. The approach treats floating-point representations as information channels and seeks to allocate precision and rounding choices to minimize information loss under a given computational budget.

Origins and scope: The concept emerged in academic discussions at the intersection of numerical analysis and information theory in the late 2010s. It is not an industry standard but has influenced research into adaptive precision and error budgeting. The framework provides a formalism for describing how rounding, truncation, and representation limits affect information retention, with emphasis on worst-case and average-case scenarios.

Key ideas: An information-theoretic objective guides precision management, aiming to maximize mutual information between input and output under resource constraints. Adaptive precision allocates bits where they matter most, while error budgeting distributes allowable discrepancy across a computation. Techniques such as compensated arithmetic, stochastic rounding, and control-theory–driven schedulers are commonly discussed within the framework.

Implementation and tools: No universal implementation exists; instead, prototypes and research prototypes describe APIs for integrating precision control into numeric kernels, enabling dynamic format selection, precision budgeting, and monitoring of information loss. Some proposals envision inclusion in high-performance computing runtimes or machine-learning inference stacks.

Applications and limitations: The approach targets scientific simulations, data analysis pipelines, and real-time systems requiring efficient yet information-rich computations. Benefits include improved accuracy per bit and reduced data movement in some workloads, while overhead and integration complexity can be substantial, and effectiveness varies by application.

See also: floating-point arithmetic, numerical analysis, stochastic rounding, information theory, precision management, error budgeting.