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The current trend for deep learning has come with an enormous computational need for billions of Multiply-Accumulate (MAC) operations per inference. Fortunately, reduced precision has demonstrated large benefits with low impact on accuracy, paving the way ...
To design faster and more energy-efficient systems, numerous inexact arithmetic operators have been proposed, generally obtained by modifying the logic structure of conventional circuits. However, as the quality of service of an application has to be ensur ...
To design faster and more energy-efficient systems, numerous inexact arithmetic operators have been proposed, generally obtained by modifying the logic structure of conventional circuits. However, as the quality of service of an application has to be ensur ...
Energy-efficiency is a critical concern for many systems, ranging from Internet of things objects and mobile devices to high-performance computers. Moreover, after 40 years of prosperity, Moore's law is starting to show its economic and technical limits. N ...
Worst-case design is used in IoT devices and high performance data centers to ensure reliability, leading to a power efficiency loss. Recently, approximate computing has been proposed to trade off accuracy for efficiency. In this paper, we use Inexact Spec ...
Ieee2017
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This paper introduces a novel method for designing approximate circuits by fabricating and exploiting false timing paths, i.e. critical paths that cannot be logically activated. This allows to strongly relax timing constraints while guaranteeing minimal an ...
2018
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In this paper, the hardware acceleration of a tone-mapping algorithm for High-Dynamic-Range image processing is presented. Starting from the C++ source code, High-Level Synthesis has been performed using Xilinx SDSoC for a Xilinx Zynq SoC device. After an ...
IEEE2018
Density, speed and energy efficiency of integrated circuits have been increasing exponentially for the last four decades following Moore's law. However, power and reliability pose several challenges to the future of technology scaling. Approximate computin ...
In most robotic and biomedical applications, the interest for real-time embedded systems with tactile ability has been growing. For example in prosthetics, a dedicated portable system is needed for developing wearable devices. The main challenges for such ...
The current trend for deep learning has come with an enormous computational need for billions of Multiply-Accumulate (MAC) operations per inference. Fortunately, reduced precision has demonstrated large benefits with low impact on accuracy, paving the way ...