Thermally optimal stop-go scheduling of task graphs with real-time constraints

Kumar, Vivek; Thiele,

doi:10.1109/aspdac.2011.5722170

Cited by 35 publications

(37 citation statements)

References 7 publications

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“…Kumar et al [9] developed a thermally optimal stopgo scheduling called JUst Sufficient Throttling (JUST) to minimize peak temperature within given makespan constraints. This scheduling is designed only for static order tasks and is not applicable for non-deterministic tasks.…”

Section: Related Workmentioning

confidence: 99%

“…Since heat generation directly originates from power consumption, DTM techniques manage the temperature via controlling the power consumption of the processor. As power consumption of processors mainly comes from dynamic and leakage power consumption, DTM techniques follow two main mechanisms, i.e., Dynamic Voltage Frequency Scaling (DVFS) [4]- [8], in which the dynamic power consumption is reduced by adjusting the supply voltage or frequency of the processor such that the temperature is lowered, and Dynamic Power Management (DPM) [2], [9]- [11], which transits the processor to sleep state to diminish the leakage power such that the on-chip temperature gets controlled.…”

Section: Introductionmentioning

confidence: 99%

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Periodic thermal management for hard real-time systems

Cheng

Huang

Chen

et al. 2015

10th IEEE International Symposium on Industrial Embedded Systems (SIES)

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Abstract-Due to growing power density, on-chip temperature increases rapidly, which has hampered the reliability and performance of modern real-time systems. This paper studies how to minimize the peak temperature for hard real-time systems under hard real-time constraints with periodic thermal management . A closed-form representation of the peak temperature for such a periodic scheme is derived to tackle this problem. Based on this closed-form and the arrival curve model which is used to model the system workload, two approaches that can derive periodic thermal management are proposed to minimize the peak temperature for a given event stream with a trade-off between complexity and accuracy. Case studies show that our approaches can achieve similar or better level of peak temperature but with two or three orders of magnitude lower computation expense compared to previous work.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Periodic thermal management for hard real-time systems

Cheng

Huang

Chen

et al. 2015

10th IEEE International Symposium on Industrial Embedded Systems (SIES)

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show abstract

“…In [69], a thermalaware scheduling algorithm with stochastic workload is presented to effectively avoid thermal emergencies by reducing peak operating temperature. In [61], Kumar et al…”

Section: Related Workmentioning

confidence: 99%

Power and Thermal Aware Scheduling for Real-time Computing Systems

Huang¹

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Over the past few decades, we have been enjoying tremendous benefits thanks to the revolutionary advancement of computing systems, driven mainly by the remarkable semiconductor technology scaling and the increasingly complicated processor architecture. However, the exponentially increased transistor density has directly led to exponentially increased power consumption and dramatically elevated system temperature, which not only adversely impacts the system's cost, performance and reliability, but also increases the leakage and thus the overall power consumption. Today, the power and thermal issues have posed enormous challenges and threaten to slow down the continuous evolvement of computer technology. Effective power/thermal-aware design techniques are urgently demanded, at all design abstraction levels, from the circuit-level, the logic-level, to the architectural-level and the system-level.In this dissertation, we present our research efforts to employ real-time scheduling techniques to solve the resource-constrained power/thermal-aware, design-optimization problems. In our research, we developed a set of simple yet accurate system-level models to capture the processor's thermal dynamic as well as the interdependency of leakage power consumption, temperature, and supply voltage. Based on these models, we investigated the fundamental principles in power/thermal-aware scheduling, and developed real-time scheduling techniques targeting at a variety of design objectives, including peak temperature minimization, overall energy reduction, and performance v maximization.The novelty of this work is that we integrate the cutting-edge research on power and thermal at the circuit and architectural-level into a set of accurate yet simplified system-level models, and are able to conduct system-level analysis and design based on these models. The theoretical study in this work serves as a solid foundation for the guidance of the power/thermal-aware scheduling algorithms development in practical computing systems.

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“…Some researches [9,125,44] take the temperature and leakage interdependency into consideration to optimize the total energy consumption. Some other approaches [20,62] seek to minimize the peak temperature at run time. There are also some other researches that studied the thermal-aware performance maximization problems [18].…”

Section: Related Workmentioning

confidence: 99%

“…A few other approaches [20,62] seek to minimize the peak temperature at run-time. There are also some researches that studied the thermal aware performance maximization problems [18,134,136].…”

Section: Related Workmentioning

confidence: 99%

Practical Dynamic Thermal Management on Intel Desktop Computer

Quan

Liu

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Professor Gang Quan, Major ProfessorFueled by increasing human appetite for high computing performance, semiconductor technology has now marched into the deep sub-micron era. As transistor size keeps shrinking, more and more transistors are integrated into a single chip. This has increased tremendously the power consumption and heat generation of IC chips. The rapidly growing heat dissipation greatly increases the packaging/cooling costs, and adversely affects the performance and reliability of a computing system. In addition, it also reduces the processor's life span and may even crash the entire computing system. Therefore, dynamic thermal management (DTM) is becoming a critical problem in modern computer system design.Extensive theoretical research has been conducted to study the DTM problem.However, most of them are based on theoretically idealized assumptions or simplified models. While these models and assumptions help to greatly simplify a complex problem and make it theoretically manageable, practical computer systems and applications must deal with many practical factors and details beyond these models or assumptions.The goal of our research was to develop a test platform that can be used to validate theoretical results on DTM under well-controlled conditions, to identify the limitations of existing theoretical results, and also to develop new and practical DTM techniques. This dissertation details the background and our research efforts in this v endeavor. Specifically, in our research, we first developed a customized test platform based on an Intel desktop. We then tested a number of related theoretical works and examined their limitations under the practical hardware environment. With these limitations in mind, we developed a new reactive thermal management algorithm for single-core computing systems to optimize the throughput under a peak temperature constraint. We further extended our research to a multicore platform and developed an effective proactive DTM technique for throughput maximization on multicore processor based on task migration and dynamic voltage frequency scaling technique. The significance of our research lies in the fact that our research complements the current extensive theoretical research in dealing with increasingly critical thermal problems and enabling the continuous evolution of high performance computing systems.

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Thermally optimal stop-go scheduling of task graphs with real-time constraints

Cited by 35 publications

References 7 publications

Periodic thermal management for hard real-time systems

Periodic thermal management for hard real-time systems

Power and Thermal Aware Scheduling for Real-time Computing Systems

Practical Dynamic Thermal Management on Intel Desktop Computer

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