TempoMP: Integrated prediction and management of temperature in heterogeneous MPSoCs

Sharifi,; Ayoub,; Rosing,

doi:10.1109/date.2012.6176542

Cited by 21 publications

(16 citation statements)

References 24 publications

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“…Specifically, for the dynamic power, we know that it is proportional to the square of supply voltage and linearity of working frequency. We assume that the working frequency is linearly proportional to supply voltage, thus the power consumption of the i-th core (P i ) under running mode k i can be formulated as below [18].…”

Section: Power Modelmentioning

confidence: 99%

Real-Time Systems

Fan¹

2016

Real-Time Systems

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Since 2004, most of chip vendors have begun to shift their major focus from singlecore to multi-core architecture (W. Wolf. Signal Processing Magazine, IEEE, 26(6):50-54, 2009). One major reason of this shift is that it reaches a physical limit by scaling transistor size and increasing the clock frequency to improve the computing performance on a single-core architecture (Agarwal et al. Proceedings of the 27th International Symposium on, pages 248-259, June 2000), that is, the overall chip cannot be reached within a single clock cycle. Multi-core architecture, however, brings innovative and promising opportunities to further improve the computing performance. By providing multiple processing cores on a single chip, multi-core systems can dramatically increase the computing performance and mitigate the power and thermal issues with the same performance achievement as single-core systems. As multi-core architecture has been more and more dominant in the industrial market, there is an urgent demand for effective and efficient techniques for the design of multi-core systems.In this chapter, we first analyze the thermal behavior on multi-core real-time systems by taking the heat transfer among different cores into consideration. Then we analyze the energy consumption for a given speed scheduling on multi-core systems.

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Section: Power Modelmentioning

confidence: 99%

Real-Time Systems

Fan¹

2016

Real-Time Systems

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“…T represents a temperature vector while T represents a temperature value. The thermal model used in this chapter is similar to the one used in related researches [113,123]. Figure 6.1 illustrates the thermal model for a 4-core system.…”

Section: Power Modelmentioning

confidence: 99%

Leakage Temperature Dependency Aware Real-Time Scheduling for Power and Thermal Optimization

Chaturvedi¹

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“…Otherwise, it can cause the DTM algorithms to overreact with the temperature changes, and further degrade system performance. A lot of research has been proposed to develop the temperature prediction techniques [137,131,99,106].…”

Section: Proactive Scheduling Algorithmmentioning

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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TempoMP: Integrated prediction and management of temperature in heterogeneous MPSoCs

Cited by 21 publications

References 24 publications

Real-Time Systems

Real-Time Systems

Leakage Temperature Dependency Aware Real-Time Scheduling for Power and Thermal Optimization

Practical Dynamic Thermal Management on Intel Desktop Computer

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