Lu Wan

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Several recent processor designs have proposed to enhance performance by increasing the clock frequency to the point where timing faults occur, and by adding error-correcting support to guarantee correctness. However, such Timing Speculation (TS) proposals are limited in that they assume traditional design methodologies that are suboptimal under TS. In this(More)
Traditional circuit design focuses on optimizing the static critical paths no matter how infrequently these paths are exercised dynamically. Circuit optimization is then tuned to the worst-case conditions to guarantee error-free computation but may also lead to very inefficient designs. Recently, there are processor works that over-clock the chip to achieve(More)
BACKGROUND Despite the numerous in-vitro studies on the mechanical properties and simulated injury mechanisms of the anterior talofibular ligament (ATFL) and calcaneofibular ligament (CFL), the in-vivo biomechanical behavior of these two ligaments has not yet been described. METHODS Apparent length of the ATFL and CFL was measured in four ankles in(More)
With technology scaling, the variability of device parameters continues to increase. This impacts both the performance and the temperature profile of the die turning them into a statistical distribution. To the best of our knowledge, no one has considered the impact of the statistical thermal profile during statistical analysis of the propagation delay. We(More)
Better-Than-Worst-case (BTW) design has been proposed as an alternative way to operate a circuit by deliberately allowing timing errors for rare cases and rectifying them with error correction mechanisms in order to achieve higher performance, better reliability guarantee, or lower energy consumption. This new design methodology necessitates the analysis(More)
The Better-Than-Worst-Case (BTW) design methodology is well-known for its potential to improve circuit energy efficiency, performance, and reliability. However, most existing methods do not provide sufficiently scalable solutions. Thus, we propose a new technique, C-Mine, which combines two scalable techniques, data mining and SAT solving, to provide(More)
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