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High performance and reliability are important aspects of space-based systems. In many cases, correct system functionality must be continuously monitored to ensure the validity of collected data. In this research we develop a new digital circuit which can detect minute phase differences in time-varying analog signals. These phase shifts can be determined(More)
Thermal sensors are currently deployed in processors to collect thermal information for dynamic thermal management (DTM). The calibration cost for thermal sensors can be prohibitively high as the number of on-chip sensors increases. We propose an on-line multi-sensor calibration method which combines potentially inaccurate temperature values obtained from(More)
Network virtualization has emerged as a powerful technique to deploy novel services and experimental protocols over shared network infrastructures. Although recent research has highlighted field programmable gate arrays (FPGAs) as attractive platforms for high performance network virtualization, these devices remain inaccessible to the larger networking(More)
Numerous sensors are currently deployed in modern processors to collect thermal information for fine-grained dynamic thermal management (DTM). Due to process variation and silicon aging, on-chip thermal sensors require periodic calibration before use in DTM. However, the calibration cost for thermal sensors can be prohibitively high as the number of on-chip(More)
Contemporary multi-core architectures deployed inembedded systems are expected to function near the operational limits of temperature, voltage, and device wear-out. To date, most on-chip sensing systems have been designed to collect and use sensor information for these parameters locally. In this paper, a new sensing system to enhance multi-core(More)
To maintain reliable operation, task allocation for many-core processors must consider the heat interaction of processor cores and network-on-chip routers in performing task assignment. Our approach employs <i>reinforcement learning</i>, machine learning algorithm that performs task allocation based on current core and router temperatures and a prediction(More)
Many-core architectures use large numbers of small temperature sensors to detect thermal gradients and guide thermal management schemes. In this paper a technique to identify thermal sensors which are operating outside a required accuracy is described. Unlike previous on-chip temperature estimation approaches, our algorithms are optimized to run on-line(More)
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