This paper shows that many applications exhibit execution-phase-specific sensitivity
towards approximation of the internal subcomputations. Therefore, approximation in certain …

In situ spacecraft observations are critical to our study and understanding of the various
phenomena that couple mass, momentum, and energy throughout near‐Earth space and …

Computation accuracy can be adequately tuned on the specific application requirements in
order to reduce power consumption. To give some examples, image processing and …

Approximate computing, being able to tradeoff computation quality (eg, accuracy) and
computational effort (eg, energy) for error-tolerant applications such as media processing …

Many emerging applications are inherently error-resilient and hence do not require exact
computation. In this paper, we consider the task allocation and scheduling problem for …

Iterative solvers like the Preconditioned Conjugate Gradient (PCG) method are widely-used
in compute-intensive domains including science and engineering that often impose tight …

Historically, numerical analysis has formed the backbone of supercomputing for decades by
applying mathematical models of first-principle physics to simulate the behavior of systems …

Employing algorithms of scientific computing often comes in hand with finding a trade-off
between accuracy and performance. Novel parallel hardware and algorithms only slightly …

ABSTRACT The use of Machine Learning in Artificial Intelligence is the inspiration that
shaped technology as it is today. Machine Learning has the power to greatly simplify our …

Approximate computing is a technique that exploits trade-offs between energy/performance
and quality of computed results. Such techniques have been explored at various design …