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

This paper describes a learning-based approach to the acceleration of approximate
programs. We describe the Parrot transformation, a program transformation that selects and …

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

Disciplined approximate programming lets programmers declare which parts of a program
can be computed approximately and consequently at a lower energy cost. The compiler …

Memories today expose an all-or-nothing correctness model that incurs significant costs in
performance, energy, area, and design complexity. But not all applications need high …

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

Mounting concerns over variability, defects, and noise motivate a new approach for digital
circuitry: stochastic logic, that is to say, logic that operates on probabilistic signals and so …

Approximate circuit designs allow us to tradeoff computation quality (eg, accuracy) and
computational effort (eg, energy), by exploiting the inherent error-resilience of many …

Emerging high-performance architectures are anticipated to contain unreliable components
that may exhibit soft errors, which silently corrupt the results of computations. Full detection …

The accuracy of an approximate computation is the distance between the result that the
computation produces and the corresponding fully accurate result. The reliability of the …