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192
Power provisioning for a warehousesized computer,”
- ACM SIGARCH Computer Architecture News,
, 2007
"... ABSTRACT Large-scale Internet services require a computing infrastructure that can be appropriately described as a warehouse-sized computing system. The cost of building datacenter facilities capable of delivering a given power capacity to such a computer can rival the recurring energy consumption ..."
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Cited by 450 (2 self)
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ABSTRACT Large-scale Internet services require a computing infrastructure that can be appropriately described as a warehouse-sized computing system. The cost of building datacenter facilities capable of delivering a given power capacity to such a computer can rival the recurring energy consumption costs themselves. Therefore, there are strong economic incentives to operate facilities as close as possible to maximum capacity, so that the non-recurring facility costs can be best amortized. That is difficult to achieve in practice because of uncertainties in equipment power ratings and because power consumption tends to vary significantly with the actual computing activity. Effective power provisioning strategies are needed to determine how much computing equipment can be safely and efficiently hosted within a given power budget. In this paper we present the aggregate power usage characteristics of large collections of servers (up to 15 thousand) for different classes of applications over a period of approximately six months. Those observations allow us to evaluate opportunities for maximizing the use of the deployed power capacity of datacenters, and assess the risks of over-subscribing it. We find that even in well-tuned applications there is a noticeable gap (7 -16%) between achieved and theoretical aggregate peak power usage at the cluster level (thousands of servers). The gap grows to almost 40% in whole datacenters. This headroom can be used to deploy additional compute equipment within the same power budget with minimal risk of exceeding it. We use our modeling framework to estimate the potential of power management schemes to reduce peak power and energy usage. We find that the opportunities for power and energy savings are significant, but greater at the cluster-level (thousands of servers) than at the rack-level (tens). Finally we argue that systems need to be power efficient across the activity range, and not only at peak performance levels.
Powernap: Eliminating server idle power
- In International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS
, 2009
"... Data center power consumption is growing to unprece-dented levels: the EPA estimates U.S. data centers will con-sume 100 billion kilowatt hours annually by 2011. Much of this energy is wasted in idle systems: in typical deployments, server utilization is below 30%, but idle servers still con-sume 60 ..."
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Cited by 219 (4 self)
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Data center power consumption is growing to unprece-dented levels: the EPA estimates U.S. data centers will con-sume 100 billion kilowatt hours annually by 2011. Much of this energy is wasted in idle systems: in typical deployments, server utilization is below 30%, but idle servers still con-sume 60 % of their peak power draw. Typical idle periods— though frequent—last seconds or less, confounding simple energy-conservation approaches. In this paper, we propose PowerNap, an energy-conservation approach where the entire system transitions rapidly be-tween a high-performance active state and a near-zero-power idle state in response to instantaneous load. Rather than requiring fine-grained power-performance states and complex load-proportional operation from each system com-ponent, PowerNap instead calls for minimizing idle power and transition time, which are simpler optimization goals. Based on the PowerNap concept, we develop requirements and outline mechanisms to eliminate idle power waste in en-terprise blade servers. Because PowerNap operates in low-efficiency regions of current blade center power supplies, we introduce the Redundant Array for Inexpensive Load Shar-ing (RAILS), a power provisioning approach that provides high conversion efficiency across the entire range of Power-Nap’s power demands. Using utilization traces collected from enterprise-scale commercial deployments, we demon-strate that, together, PowerNap and RAILS reduce average server power consumption by 74%.
Ensemble-level Power Management for Dense Blade Servers
- In Proceedings of the International Symposium on Computer Architecture (ISCA
, 2006
"... One of the key challenges for high-density servers (e.g., blades) is the increased costs in addressing the power and heat density associated with compaction. Prior approaches have mainly focused on reducing the heat generated at the level of an individual server. In contrast, this work proposes powe ..."
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Cited by 179 (21 self)
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One of the key challenges for high-density servers (e.g., blades) is the increased costs in addressing the power and heat density associated with compaction. Prior approaches have mainly focused on reducing the heat generated at the level of an individual server. In contrast, this work proposes power efficiencies at a larger scale by leveraging statistical properties of concurrent resource usage across a collection of systems (“ensemble”). Specifically, we discuss an implementation of this approach at the blade enclosure level to monitor and manage the power across the individual blades in a chassis. Our approach requires low-cost hardware modifications and relatively simple software support. We evaluate our architecture through both prototyping and simulation. For workloads representing 132 servers from nine different enterprise deployments, we show significant power budget reductions at performances comparable to conventional systems. 1.
VirtualPower: Coordinated Power Management in Virtualized Enterprise Systems
- In Proceedings of International Symposium on Operating System Principles (SOSP
, 2007
"... Power management has become increasingly necessary in large-scale datacenters to address costs and limitations in cooling or power delivery. This paper explores how to integrate power management mechanisms and policies with the virtualization technologies being actively deployed in these environment ..."
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Cited by 161 (12 self)
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Power management has become increasingly necessary in large-scale datacenters to address costs and limitations in cooling or power delivery. This paper explores how to integrate power management mechanisms and policies with the virtualization technologies being actively deployed in these environments. The goals of the proposed VirtualPower approach to online power management are (i) to support the isolated and independent operation assumed by guest virtual machines (VMs) running on virtualized platforms and (ii) to make it possible to control and globally coordinate the effects of the diverse power management policies applied by these VMs to virtualized resources. To attain these goals, VirtualPower extends to guest VMs ‘soft ’ versions of the hardware power states for which their policies are designed. The resulting technical challenge is to appropriately map VM-level updates made to soft power states to actual changes in the states or in the allocation of underlying virtualized hardware. An implementation of VirtualPower Management (VPM) for the Xen hypervisor addresses this challenge by provision of multiple system-level abstractions including VPM states, channels, mechanisms, and rules. Experimental evaluations on modern multicore platforms highlight resulting improvements in online power management capabilities, including minimization of power consumption with little or no performance penalties and the ability to throttle power consumption while still meeting application requirements. Finally, coordination of online methods for server consolidation with VPM management techniques in heterogeneous server systems is shown to provide up to 34% improvements in power consumption.
Mercury and Freon: Temperature Emulation and Management for Server Systems
"... Power densities have been increasing rapidly at all levels of server systems. To counter the high temperatures resulting from these densities, systems researchers have recently started work on software-based thermal management. Unfortunately, research in this new area has been hindered by the limita ..."
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Cited by 97 (9 self)
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Power densities have been increasing rapidly at all levels of server systems. To counter the high temperatures resulting from these densities, systems researchers have recently started work on software-based thermal management. Unfortunately, research in this new area has been hindered by the limitations imposed by simulators and real measurements. In this paper, we introduce Mercury, a software suite that avoids these limitations by accurately emulating temperatures based on simple layout, hardware, and componentutilization data. Most importantly, Mercury runs the entire software stack natively, enables repeatable experiments, and allows the study of thermal emergencies without harming hardware reliability. We validate Mercury using real measurements and a widely used commercial simulator. We use Mercury to develop Freon, a system that manages thermal emergencies in a server cluster without unnecessary performance degradation. Mercury will soon become available from
Energy-Efficient, Thermal-Aware Task Scheduling for Homogeneous, High Performance Computing Data Centers: A Cyber-Physical Approach
"... Abstract—High Performance Computing data centers have been rapidly growing, both in number and size. Thermal management of data centers can address dominant problems associated with cooling such as the recirculation of hot air from the equipment outlets to their inlets, and the appearance of hot spo ..."
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Cited by 76 (5 self)
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Abstract—High Performance Computing data centers have been rapidly growing, both in number and size. Thermal management of data centers can address dominant problems associated with cooling such as the recirculation of hot air from the equipment outlets to their inlets, and the appearance of hot spots. In this paper, we show through formalization that minimizing the peak inlet temperature allows for the lowest cooling power needs. Using a low-complexity, linear heat recirculation model, we define the problem of minimizing the peak inlet temperature within a data center through task assignment (MPIT-TA), consequently leading to minimal cooling requirement. We also provide two methods to solve the formulation, XInt-GA, which uses a genetic algorithm and XInt-SQP, which uses sequential quadratic programming. Results from small-scale data center simulations show that solving the formulation leads to an inlet temperature distribution that, compared to other approaches, is 2 °C to 5 °C lower and achieves about 20%-30 % cooling energy savings at common data center utilization rates. Moreover, our algorithms consistently outperform MinHR, a recirculation-reducing task placement algorithm in the literature.
Full-system power analysis and modeling for server environments
- In Workshop on Modeling Benchmarking and Simulation (MOBS
, 2006
"... Abstract — The increasing costs of power delivery and cooling, as well as the trend toward higher-density computer systems, have created a growing demand for better power management in server environments. Despite the increasing interest in this issue, little work has been done in quantitatively und ..."
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Cited by 75 (1 self)
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Abstract — The increasing costs of power delivery and cooling, as well as the trend toward higher-density computer systems, have created a growing demand for better power management in server environments. Despite the increasing interest in this issue, little work has been done in quantitatively understanding power consumption trends and developing simple yet accurate models to predict full-system power. We study the component-level power breakdown and variation, as well as temporal workload-specific power consumption of an instrumented power-optimized blade server. Using this analysis, we examine the validity of prior adhoc approaches to understanding power breakdown and quantify several interesting trends important for power modeling and management in the future. We also introduce Mantis, a nonintrusive method for modeling full-system power consumption and providing real-time power prediction. Mantis uses a onetime calibration phase to generate a model by correlating AC power measurements with user-level system utilization metrics. We experimentally validate the model on two server systems with drastically different power footprints and characteristics (a low-end blade and high-end compute-optimized server) using a variety of workloads. Mantis provides power estimates with high accuracy for both overall and temporal power consumption, making it a valuable tool for power-aware scheduling and analysis. I.
Delivering Energy Proportionality with Non Energy-Proportional Systems – Optimizing the Ensemble
"... With power having become a critical issue in the operation of data centers today, there has been an increased push towards the vision of “energy-proportional computing”, in which no power is used by idle systems, very low power is used by lightly loaded systems, and proportionately higher power at h ..."
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Cited by 61 (0 self)
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With power having become a critical issue in the operation of data centers today, there has been an increased push towards the vision of “energy-proportional computing”, in which no power is used by idle systems, very low power is used by lightly loaded systems, and proportionately higher power at higher loads. Unfortunately, given the state of the art of today’s hardware, designing individual servers that exhibit this property remains an open challenge. However, even in the absence of redesigned hardware, we demonstrate how optimization-based techniques can be used to build systems with off-the-shelf hardware that, when viewed at the aggregate level, approximate the behavior of energy-proportional systems. This paper explores the viability and tradeoffs of optimization-based approaches using two different case studies. First, we show how different power-saving mechanisms can be combined to deliver an aggregate system that is proportional in its use of server power. Second, we show early results on delivering a proportional cooling system for these servers. When compared to the power consumed at 100 % utilization, results from our testbed show that optimization-based systems can reduce the power consumed at 0 % utilization to 15 % for server power and 32 % for cooling power. 1
Exploiting platform heterogeneity for power efficient data centers
- In Proceedings of the IEEE International Conference on Autonomic Computing (ICAC
, 2007
"... It has recently become clear that power management is of critical importance in modern enterprise computing environments. The traditional drive for higher performance has influenced trends towards consolidation and higher densities, artifacts enabled by virtualization and new small form factor serve ..."
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Cited by 57 (4 self)
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It has recently become clear that power management is of critical importance in modern enterprise computing environments. The traditional drive for higher performance has influenced trends towards consolidation and higher densities, artifacts enabled by virtualization and new small form factor server blades. The resulting effect has been increased power and cooling requirements in data centers which elevate ownership costs and put more pressure on rack and enclosure densities. To address these issues, in this paper, we enable power-efficient management of enterprise workloads by exploiting a fundamental characteristic of data centers: “platform heterogeneity”. This heterogeneity stems from the architectural and management-capability variations of the underlying platforms. We define an intelligent workload allocation method that leverages heterogeneity characteristics and efficiently maps workloads to the best fitting platforms, significantly improving the power efficiency of the whole data center. We perform this allocation by employing a novel analytical prediction layer that accurately predicts workload power/performance across different platform architectures and power management capabilities. This prediction infrastructure relies upon platform and workload descriptors that we define as part of our work. Our allocation scheme achieves on average 20 % improvements in power efficiency for representative heterogeneous data center configurations, highlighting the significant potential of heterogeneity-aware management. 1
Virtual machine hosting for networked clusters: Building the foundations for ’autonomic’ orchestration
- In Proc. VTDC ’06
, 2006
"... Virtualization technology offers powerful resource management mechanisms, including performance-isolating resource schedulers, live migration, and suspend/resume. But how should networked virtual computing systems use these mechanisms? A grand challenge is to devise practical policies to drive these ..."
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Cited by 55 (8 self)
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Virtualization technology offers powerful resource management mechanisms, including performance-isolating resource schedulers, live migration, and suspend/resume. But how should networked virtual computing systems use these mechanisms? A grand challenge is to devise practical policies to drive these mechanisms in a self-managing or “autonomic” system, without relying on human operators. This paper explores architectural and algorithmic issues for resource management policy and orchestration in Shirako, a system for on-demand leasing of shared networked resources in federated clusters. Shirako enables a flexible factoring of resource management functions across the participants in a federated system, to accommodate a range of models of distributed virtual computing. We present extensions to Shirako to provision fine-grained virtual machine “slivers ” and drive virtual machine migration. We illustrate the interactions of provisioning and placement/migration policies, and their impact. 1
