The challenging deployment of compute-intensive applications from domains such as
Artificial Intelligence (AI) and Digital Signal Processing (DSP), forces the community of …

When a computational task tolerates a relaxation of its specification or when an algorithm
tolerates the effects of noise in its execution, hardware, system software, and programming …

We present both an overview and a perspective of recent experimental advances and
proposed new approaches to performing computation using memristors. A memristor is a 2 …

Approximate computing is an advanced computational technique that trades the accuracy of
computation results for better utilization of system resources. It has emerged as a new …

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 …

IoT devices play a fundamental role in the machine learning (ML) application pipeline, as
they collect rich data for model training using sensors. However, this process can be affected …

Trade-offs between accuracy and efficiency pervade law, public health, and other non-
computing domains, which have developed policies to guide how to balance the two in …

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 …

Energy-harvesting devices—which operate solely on energy collected from their
environment—have brought forth a new paradigm of intermittent computing. These devices …

Precision tuning trades accuracy for speed and energy savings, usually by reducing the data
width, or by switching from floating point to fixed point representations. However, comparing …