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

The use of reduced precision to improve performance metrics such as computation latency
and power consumption is a common practice in the embedded systems field. This practice …

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 …

Approximate computing has emerged as a new paradigm to reduce the resources (eg,
design area and power) required to realize digital systems at the expense of a negligible or …

This work is a survey on approximate computing and its impact on fault tolerance, especially
for safety-critical applications. It presents a multitude of approximation methodologies, which …

Several applications may trade-off output quality for energy efficiency by computing only an
approximation of their output. Current approaches to software-based approximate …

We introduce a task-based programming model and runtime system that exploit the
observation that not all parts of a program are equally significant for the accuracy of the end …

With the end of conventional CMOS scaling, efficient resiliency solutions are needed to
address the increased likelihood of hardware errors. Silent data corruptions (SDCs) are …

The unprecedented progress in computational technologies led to a substantial proliferation
of artificial intelligence applications, notably in the era of big data and IoT devices. In the …

Memory approximation techniques are commonly limited in scope, targeting individual
levels of the memory hierarchy. Existing approximation techniques for a full memory …