Approximate computing has emerged as a new paradigm for high-performance and energy-
efficient design of circuits and systems. For the many approximate arithmetic circuits …

Deep neural networks (DNNs) have been widely used in classification due to their high
accuracy. The softmax function is one of the important non-linear functions in DNNs …

Leveraging the inherent error tolerance of a vast number of application domains that are
rapidly growing, approximate computing arises as a design alternative to improve the …

Racetrack memory (RM) techniques have become promising solutions to resolve the
memory wall issue as they increase memory density, reduce energy consumption and are …

We propose approximate dividers with near-zero error bias for both integer and floating-
point numbers. The integer divider, INZeD, is designed using a novel, analytically deduced …

Energy efficiency is one of the most crucial constraints that dictate performance, lifetime,
form factor, and cost in modern computing system design. However, the energy efficiency …

In this paper, an adaptive approximation approach is proposed for the design of a divider
and a square root (SQR) circuit. In this design, the division/SQR is computed by using a …

The rapid updates in error-resilient applications along with their quest for high throughput
has motivated designing fast approximate functional units for field-programmable gate …

Approximate computing can be used in error-resilient applications to reduce power
consumption and increase overall circuit performance. This article introduces two …

Approximate computing can significantly improve the energy efficiency of arithmetic
operations in error-resilient applications. In this paper, we propose an approximate divider …