The paper provides an overview of the neural networks implementation current state, their
methods of execution, and the Intel® OpenVINO™ Toolkit for executing neural networks on …

Deep neural networks (DNNs) have become an enabling component for a myriad of artificial
intelligence applications. DNNs have shown sometimes superior performance, even …

Reduced precision number formats have become increasingly popular in various fields of
computational science, as they offer the potential to enhance energy efficiency, reduce …

The use of approximate communication has emerged as a promising approach for
enhancing the efficiency of communication in parallel computer systems. By sending …

Posit arithmetic has attracted a lot of attention as a promising alternative to the IEEE754
floating-point number representation thanks to its advantages such as higher accuracy and …

IEEE-754 is the de-facto standard for the implementation of floating-point number systems in
hardware. With the rise of machine-learning and mixed-precision computation, applications …

This paper presents a new approach for support vector filtering to accelerate the training
process of support vector machines (SVMs). It is based on the Sets-of-Real-Numbers …

POSIT offers a wider dynamic range when compared to floating-point (FP) formats with
lesser number of bits. Such data formats are required to address the need for low-bit high …

For many decades, IEEE floating-point formats are used as the golden numeric formats for
many applications including signal processing, linear algebra evaluation, and other …

The demand to deploy deep learning models on edge devices has recently increased due to
their pervasiveness, in applications ranging from healthcare to precision agriculture …