Approximate computing can be employed for an emerging class of applications from various
domains such as multimedia, machine learning and computer vision. The approximated …

Approximate computing trades off computation quality with effort expended, and as rising
performance demands confront plateauing resource budgets, approximate computing has …

Approximate computing is an approach where reduced accuracy of results is traded off for
increased speed, throughput, or both. Loss of accuracy is not permissible in all computing …

Energy efficiency is a key concern in the design of modern computer systems. One
promising approach to energy-efficient computation, approximate computing, trades off …

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 is claimed to be a powerful knob for alleviating the peak power and
energy-efficiency issues. However, providing a consistent benchmark suit with diverse …

Approximate computing trades off accuracy for better performance and energy efficiency. It
offers promising optimization opportunities for a wide variety of modern applications, from …

Approximate computing, where computation accuracy is traded off for better performance or
higher data throughput, is one solution that can help data processing keep pace with the …

Approximate computing is an emerging design paradigm that exploits the intrinsic ability of
applications to produce acceptable outputs even when their computations are executed …

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