Nonconventional Computer Arithmetic Circuits, Systems and Applications

Abstract

Arithmetic plays a major role in a computer?s performance and efficiency. Building new computing platforms supported by the traditional binary arithmetic and silicon-based technologies to meet the requirements of today?s applications is becoming increasingly more challenging, regardless whether we consider embedded devices or high-performance computers. As a result, a significant amount of research effort has been devoted to the study of nonconventional number systems to investigate more efficient arithmetic circuits and improved computer technologies to facilitate the development of computational units that can meet the requirements of applications in emergent domains. This paper presents an overview of the state of the art in nonconventional computer arithmetic. Several different alternative computing models and emerging technologies are analyzed, such as nanotechnologies, superconductor devices, and biological- and quantum-based computing, and their applications to multiple domains are discussed. A comprehensive approach is followed in a survey of the logarithmic and residue number systems, the hyperdimensional and stochastic computation models, and the arithmetic for quantum- and DNA-based computing systems and techniques for approximate computing. Technologies, processors and systems addressing these nonconventional computer arithmetic systems are also reviewed, taking into consideration some of the most prominent applications, such as deep learning or postquantum cryptography. In the end, some conclusions are drawn, and directions for future research on nonconventional computer arithmetic are discussed.