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Imprecise adders are implemented to improve the performance and power consumption of arithmetic circuits with forgivable inaccurate results. These types of designs are extensively used in digital computer systems for approximate computing. One of the challenges in designing imprecise adders is evaluation of output quality. Currently, the most popular technique to evaluate the approximate designs are...
Approximate computing techniques have paved new paths to get substantial improvement in speed and power efficiency by making a trade-off with the accuracy of computations in inherently error tolerant applications, like from image and video processing domains. The accuracy requirements of various applications can differ from each other. Even within a same application different computationscan have...
Approximate Computing is revealing a new design paradigm which trades algorithms precision off for enhancing performance parameters, commonly energy consumption and computation time. Applications which are characterized by the inherent resiliency property tolerate some quality loss, w. r. t. the optimal result. The approximation is accomplished by combining substitutions of fully-precise block operations...
Stochastic computing (SC) encodes data in the signal probabilities associated with pseudo-random bit-streams. It enables very low-area and low-power arithmetic operations using standard VLSI circuits, it is also highly error-tolerant. While addition, subtraction and multiplication have extremely simple SC implementations, this is not true for division. Known stochastic dividers employ sequential logic...
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