Approximate computing has gained research attention recently as a way to increase energy
efficiency and/or performance by exploiting some applications' intrinsic error resiliency …

Approximate computing is gaining traction as a computing paradigm for data analytics and
cognitive applications that aim to extract deep insight from vast quantities of data. In this …

Approximate computing, where computation quality is traded off for better performance
and/or energy savings, has gained significant tractions from both academia and industry …

As one of the most promising energy-efficient computing paradigms, approximate computing
has gained a lot of research attention in the past few years. This paper presents a survey of …

The intrinsic error resilience exhibited by emerging application domains enables new
avenues for energy optimization of computing systems, namely, the introduction of a small …

Approximate computing, which tackles tradeoff between computation quality (eg, accuracy)
and computation efforts, is becoming a promising technique to improve performance for …

Diminishing benefits from technology scaling have pushed designers to look for new
sources of computing efficiency. Multicores and heterogeneous accelerator-based …

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 …

Approximate computing is the idea that systems can gain performance and energy efficiency
if they expend less effort on producing a “perfect” answer. Approximate computing …

Approximate computing environments trade off computational accuracy for improvements in
performance, energy, and resiliency cost. For widespread adoption of approximate …