Approximate computing is an emerging design paradigm that enables highly efficient
hardware and software implementations by exploiting the inherent resilience of applications …

Neuromorphic algorithms, which are comprised of highly complex, large-scale networks of
artificial neurons, are increasingly used for a variety of recognition, classification, search and …

Approximate computing has emerged as a new design paradigm that exploits the inherent
error resilience of a wide range of application domains by allowing hardware …

Approximate computing leverages the intrinsic resilience of applications to inexactness in
their computations, to achieve a desirable trade-off between efficiency (performance or …

Algorithms from several interesting application domains exhibit the property of inherent
resilience to" errors" from extrinsic or intrinsic sources, offering entirely new avenues for …

Many applications produce acceptable results when their underlying computations are
executed in an approximate manner. For such applications, approximate circuits enable …

Advances in deep neural networks (DNNs) and the availability of massive real-world data
have enabled superhuman levels of accuracy on many AI tasks and ushered the explosive …

Applications from several application domains exhibit the property of inherent application
resilience, offering entirely new avenues for performance and power optimization by …

Well over a decade ago, many believed that an engine of growth driving the semiconductor
and computing industries---captured nicely by Gordon Moore's remarkable prophecy …

The current state-of-the-art approximate adders are mostly ASIC-based, ie, they focus solely
on gate and/or transistor level approximations (eg, through circuit simplification or …