Thermal-Aware Global Real-Time Scheduling on Multicore Systems

Fisher, Nathan; Chen, Jian-Jia; Wang, Shengquan; Thiele, Lothar

doi:10.1109/rtas.2009.34

Cited by 81 publications

(83 citation statements)

References 23 publications

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“…Zhang et al [35] take time into account and give an approximation algorithm for voltage frequency scaling. Fisher et al [10] use the Fourier's cooling model to model cooling and heating phenomena, and develop algorithms for frequency scaling. Choi et al [6] observe that the rise-and fall-times of on-chip temperatures are typically an order of magnitude larger than the OS scheduler ticks, and develop an OS-level scheduler to balance the heat and avoid formation of hotspots.…”

Section: Related Workmentioning

confidence: 99%

Algorithms for the Thermal Scheduling Problem

Mukherjee

Khuller

Deshpande

2013

2013 IEEE 27th International Symposium on Parallel and Distributed Processing

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Abstract-The energy costs for cooling a data center constitute a significant portion of the overall running costs. Thermal imbalance and hot spots that arise due to imbalanced workloads lead to significant wasted cooling effort -in order to ensure that no equipment is operating above a certain temperature, the data center may be cooled more than necessary. Therefore it is desirable to schedule the workload in a data center in a thermally aware manner, assigning jobs to machines not just based on local load of the machines, but based on the overall thermal profile of the data center. This is challenging because of the spatial cross-interference between machines, where a job assigned to a machine may impact not only that machine's temperature, but also nearby machines.Here, we continue formal analysis of the thermal scheduling problem that we initiated recently [25]. In that work, the notion of effective load of a machine which is a function of the local load on the machine as well as the load on nearby machines, was introduced, and optimal scheduling policies for a simple model (where cross-effects are restricted within a rack) were presented, under the assumption that jobs can be split among different machines. Here we consider the more realistic problem of integral assignment of jobs, and allow for cross-interference among different machines in adjacent racks in the data center. The integral assignment problem with cross-interference is NP-hard, even for a simple two machine model. We consider three different heat flow models, and give constant factor approximation algorithms for maximizing the number (or total profit) of jobs assigned in each model, without violating thermal constraints. We also consider the problem of minimizing the maximum temperature on any machine when all jobs need to be assigned, and give constant factor algorithms for this problem.

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Section: Related Workmentioning

confidence: 99%

Algorithms for the Thermal Scheduling Problem

Mukherjee

Khuller

Deshpande

2013

2013 IEEE 27th International Symposium on Parallel and Distributed Processing

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“…Liu et al [72] show that using the linear approximation is an effective way to accurately estimate the leakage power over the common operating temperature range of real-time ICs. A number of exiting works (such as [31,42,27]) adopt simple leakage/temperature dependency models that assume the leakage current changes linearly only with temperature. However, as shown in Chapter 3, the leakage models ignoring the effect of supply voltage can lead to results deviated far away from the actual values.…”

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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“…There has been extensive theoretical researches, which focus on dynamic thermal management for the single core microprocessor, which have been published in the literature [104,79]. For example, Wang et al proposed a scheduling algorithm that can exploit the flexibility of single core platform at low temperature by deriving an ideally preferred speed [35]. Zhang [135] In this chapter, we investigate the effectiveness of several dynamic thermal management techniques based on our practical hardware platform.…”

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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Thermal-Aware Global Real-Time Scheduling on Multicore Systems

Cited by 81 publications

References 23 publications

Algorithms for the Thermal Scheduling Problem

Algorithms for the Thermal Scheduling Problem

Power and Thermal Aware Scheduling for Real-time Computing Systems

Practical Dynamic Thermal Management on Intel Desktop Computer

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