The barriers to improving computers' performance have led to the emergence of new
computing paradigms and technologies. Among these, the memristors are of great concern …

Several challenges in improving the performance of computing systems have given rise to
emerging computing paradigms. One of these paradigms is approximate computing. Many …

Today's processing applications require frequent and energy-consuming data transfers
between memory and processing elements. Reducing the dimensions of Metal Oxide …

Deep neural network (DNN)-based transformer models have demonstrated remarkable
performance in natural language processing (NLP) applications. Unfortunately, the unique …

As the demand for computational power increases drastically, traditional solutions to
address those needs struggle to keep up. Consequently, there has been a proliferation of …

This paper explores the integration and application of Approximate Computing (AxC)
approaches to Machine Learning (ML), especially Deep Learning (DL) models. We focus on …

Nowadays, a wide range of applications can tolerate certain computational errors. Hence,
approximate computing has become one of the most attractive topics in computer …

To alleviate the Von Neumann bottleneck, new technologies and computing paradigms
have been a hot topic in research and development in recent years. Memristors offer new …

Due to the ever-increasing complexity of computing tasks, emerging computing paradigms
that increase efficiency, such as approximate computing, are gaining momentum. However …

As the demand for increased performance and reduced energy consumption continues to
grow, Quality of Service (QoS) adjustment approaches offer an effective way to tackle those …