The rapid growth of demanding applications in domains applying multimedia processing
and machine learning has marked a new era for edge and cloud computing. These …

The challenging deployment of compute-intensive applications from domains such as
Artificial Intelligence (AI) and Digital Signal Processing (DSP), forces the community of …

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning
(DL) is already present in many applications ranging from computer vision for medicine to …

Approximate multiplication is a common operation used in approximate computing methods
for high performance and low power computing. Power-efficient circuits for approximate …

Multiplication is one of the widely used arithmetic operations in a variety of applications,
such as image/video processing and machine learning. FPGA vendors provide high …

This paper presents an architectural-space exploration methodology for designing
approximate multipliers. Unlike state-of-the-art, our methodology generates various design …

In the Machine Learning era, Deep Neural Networks (DNNs) have taken the spotlight, due to
their unmatchable performance in several applications, such as image processing, computer …

Libraries of approximate circuits are composed of fully characterized digital circuits that can
be used as building blocks of energy-efficient implementations of hardware accelerators …

Approximate recursive multipliers exhibit low-power operation because they are designed
using smaller power-efficient approximate multiplier blocks. These building blocks can be …

When a computational task tolerates a relaxation of its specification or when an algorithm
tolerates the effects of noise in its execution, hardware, system software, and programming …