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This article proposes a methodology for critical path selection and delay sensor insertion for aging monitoring in field-programmable gate arrays (FPGAs). The aging information can be used to reconfigure FPGAs to achieve better performance or wear leveling. To filter out the paths aging less aggressively, our methodology decides based on both physical-level parameters [e.g., path delay, process variation, temperature, static stress (duty cycle), and dynamic stress (switching activity) as well as aging-relevant parameters (e.g., fan-out, and endpoint physical location)]. After selection of an optimal set of paths, age sensors, introduced in our earlier work, are placed in a distributed fashion throughout the FPGA area to provide aging information of its various parts as they are being used. Accurate aging models for FPGAs are required to determine the contribution of the above-mentioned parameters in aging. In this article, ASICs’ aging models are adapted for FPGAs through measurement-based fitting approach. The experimental results using various benchmarks reveal that our algorithm selects paths with a minimum error. [ABSTRACT FROM AUTHOR]

In this article, we propose a fine-grained FPGA aging mitigation method. Our method focuses on Look Up Tables (LUTs) on which Boolean functions are mapped. Based on our observations, for any configuration, even if it is carefully selected, a number of LUT transistors experience severe stress rates. Therefore, an algorithm is presented to select several alternative configurations for each LUT. Alternative configurations are obtained by LUT input reordering. These alternative configurations are rotationally loaded into the FPGA. Experimental results shows that our method achieves 263 and 14.1 percent Mean Time To Failure (MTTF) improvement for Hot Carrier Injection (HCI) and Bias Temperature Instability (BTI), respectively. Additionally, due to changing only local routings, our method imposes up to 1 percent performance overhead to the systems. [ABSTRACT FROM AUTHOR]

This paper proposes a highly scalable sensor design for late transition detection in FPGA based platforms. Transition delays occur because of aging mechanisms such as Biased Temperature Instability (BTI) and Hot Carrier Injection (HCI). We propose a sensor clock (SCLK) that is a function of minimum slack time of a set of paths selected for age monitoring. There will be one such clock for many sensors as are needed in an entire FPGA. Our proposed sensor architecture makes it possible for a single SCLK to be shared by all sensors. Additionally, the proposed sensor occupies one slice (basic FPGA logic block), which leads to low area, power, and performance overhead. Using Artix-7-based board, experimental results demonstrate that the proposed aging sensor detects aging earlier than existing sensors and provides less power and performance overheads. [ABSTRACT FROM AUTHOR]

There has been a growing interest in assessing the condition and quality of life in older adult population, and factors contributing to it. In this context, fear of falling syndrome is introduced as one of the main factors that can affect the quality of life in the general adult population. However, little is known about the relationship between fear of falling and other disorders in older adults, particularly among the Middle East population. Here we investigated the associations between fear of falling and anxiety and depression disorders. A standardized questionnaire was used to assess sociodemographic variables and physical health condition. Subsequently, fear of falling and anxiety and depression scales were assessed using the Falls Efficacy Scale International and the Hospital Anxiety Depression Scale, respectively. Our results highlighted the high risk of having anxiety and depression disorders among older adults. The findings also indicate that physical and mental health disorders play a significant role in incident fear of falling. Therefore, improving mental health might lend controlling fear of falling syndrome, which then preventing falls incident and subsequent injury in older adult population. [ABSTRACT FROM AUTHOR]