Optimization power consumption model of reliability-aware GPU clusters
The Journal of Supercomputing
Power-aware fixed priority scheduling for sporadic tasks in hard real-time systems
Journal of Systems and Software
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The negative impact of the popular energy management technique Dynamic Voltage and Frequency Scaling (DVFS) on the reliability of real-time embedded systems, in terms of increased transient fault rates, has been recently identified. As a result, recent research literature includes a number of solutions within the so-called Reliability-Aware Power Management (RA-PM) framework, where the aim is to preserve the system's original reliability. In this research effort, we propose a more general framework where the aim is to achieve arbitrary reliability levels that may vary for each periodic task. A critical component of our solution is the use of dynamically allocated recoveries: we show that providing a relatively modest recovery allowance to a given periodic task helps to achieve surprisingly high reliability levels as long as these allowances can be reclaimed on-demand during the hyper period. We propose a pseudo-polynomial time feasibility test, as well as static and dynamic algorithms to determine the recovery allowance and frequency assignments to minimize energy consumption while satisfying timing and reliability constraints. Our experimental evaluation points to the significant gain potential of the new framework in terms of both energy and reliability figures.