Overview of the hardware implementation of devices using Posit number system

Abstract

The modern development of computer computing is accompanied by increasing demands for numerical representation accuracy, energy efficiency, and hardware optimization. The traditional floating-point format IEEE 754, which has served as the fundamental standard in numerical computations for decades, reveals a number of limitations that become critical under new technological challenges. In particular, issues such as excessive hardware complexity, limited accuracy, and inefficient utilization of computational resources remain problematic.
The Posit arithmetic is considered a promising alternative to classical approaches. Its conceptual features make it possible to enhance numerical accuracy, reduce hardware costs, and achieve a better balance between performance and energy efficiency. This makes the Posit system a relevant subject of investigation in such fields as deep learning, embedded systems, and high-performance computing.
However, the practical implementation of Posit arithmetic at the hardware level requires in-depth analysis. The viability and scalability of this new number representation system are determined by the efficiency of hardware architectures capable of providing the required levels of accuracy, performance, and robustness against computational errors.
In the main part of this article, prepared within the framework of obtaining the degree of Doctor of Philosophy, the fundamentals of Posit arithmetic, its structure, advantages, and challenges in comparison with IEEE 754 are described.This is followed by a detailed examination of hardware implementations of Posit arithmetic units. Applications in deep learning, accuracy and efficiency analyses, robustness studies, and error investigations will be considered. The review concludes with a summary of the key findings and implications for future research.