Amip J. Shah

Capacity planning and power management to exploit sustainable energy

This paper describes an approach for designing a power management plan that matches the supply of power with the demand for power in data centers. Power may come from the grid, from local renewable sources, and possibly from energy storage subsystems. The supply of renewable power is often time-varying in a manner that depends on the source that provides the power, the location of power generators, and the weather conditions. The demand for power is mainly determined by the time-varying workloads hosted in the data center and the power management policies implemented by the data center. A case study demonstrates how our approach can be used to design a plan for realistic and complex data center workloads. The study considers a data centers deployment in two geographic locations with different supplies of power. Our approach offers greater precision than other planning methods that do not take into account time-varying power supply and demand and data center power management policies.

On energy efficiency for enterprise and data center networks

In recent years, there has been intense focus on increasing the energy efficiency of IT infrastructure. We advocate the need to consider energy consumption holistically over the entire lifetime of these devices. Life cycle energy considerations include a number of factors, of which operational energy consumption is just one. Of all the IT components, networks have received relatively little attention when it comes to energy efficient operation, and even that has been too focused on operational power consumption. In this article, we describe the challenges relating to life cycle energy management of network devices, present a sustainability analysis of these devices, and develop techniques to significantly reduce network operational power. A distinguishing feature of our work is that it is applicable to legacy devices, and as such can be deployed now, as opposed to waiting for new standards and products to be developed.

From Chip to Cooling Tower Data Center Modeling: Influence of Server Inlet Temperature and Temperature Rise Across Cabinet

To achieve reductions in the power consumption of the data center cooling infrastructure, the current strategy in data center design is to increase the inlet temperature to the rack, while the current strategy for energy-efficient system thermal design is to allow increased temperature rise across the rack. Either strategy, or a combination of both, intuitively provides enhancements in the coefficient of performance of the data center in terms of computing energy usage relative to cooling energy consumption. However, this strategy is currently more of an empirically based approach from practical experience, rather than a result of a good understanding of how the impact of varying temperatures and flow rates at rack level influences each component in the chain from the chip level to the cooling tower. The aim of this paper is to provide a model to represent the physics of this strategy by developing a modeling tool that represents the heat flow from the rack level to the cooling tower for an air cooled data center with chillers. This model presents the performance of a complete data center cooling system infrastructure. After detailing the model, two parametric studies are presented that illustrate the influence of increasing rack inlet air temperature, and temperature rise across the rack, on different components in the data center cooling architecture. By considering the total data center, and each components influence on the greater infrastructure, it is possible to identify the components that contribute most to the resulting inefficiencies in the heat flow from chip to cooling tower and thereby identify the components in need of possible redesign. For the data center model considered here it is shown that the strategy of increasing temperature rise across the rack may be a better strategy than increasing inlet temperature to the rack.

Towards the design and operation of net-zero energy data centers

Reduction of resource consumption in data centers is becoming a growing concern for data center designers, operators and users. Accordingly, interest in the use of renewable energy to provide some portion of a data centers overall energy usage is also growing. One key concern is that the amount of renewable energy necessary to satisfy a typical data centers power consumption can lead to prohibitively high capital costs for the power generation and delivery infrastructure, particularly if on-site renewables are used. In this paper, we introduce a method to operate a data center with renewable energy that minimizes dependence on grid power while minimizing capital cost. We achieve this by integrating data center demand with the availability of resource supplies during operation. We discuss results from the deployment of our method in a production data center.

From chip to cooling tower data center modeling: Part I Influence of server inlet temperature and temperature rise across cabinet

To achieve reductions in the power consumption of the data center cooling infrastructure, the current strategy in data center design is to increase the inlet temperature to the rack, while the current strategy for energy-efficient system thermal design is to allow increased temperature rise across the rack. Either strategy, or a combination of both, intuitively provides enhancements in the coefficient of performance (COP) of the data center in terms of computing energy usage relative to cooling energy consumption. However, this strategy is currently more of an empirically based approach from practical experience, rather than a result of a good understanding of how the impact of varying temperatures and flow rates at rack level influences each component in the chain from the chip level to the cooling tower. The aim of this paper is to provide a model to represent the physics of this strategy by developing a modeling tool that represents the heat flow from the rack level to the cooling tower for an air cooled data center with chillers. This model presents the performance of a complete data center cooling system infrastructure. After detailing the model, two parametric studies are presented that illustrate the influence of increasing rack inlet air temperature, and temperature rise across the rack, on different components in the data center cooling architecture. By considering the total data center, and each components influence on the greater infrastructure, it is possible to identify the components that contribute most to the resulting inefficiencies in the heat flow from chip to cooling tower and thereby identify the components in need of possible redesign. For the data center model considered here it is shown that the strategy of increasing temperature rise across the rack may be a better strategy than increasing inlet temperature to the rack. Part II of this work expands on this paper with further parametric studies to evaluate the robustness of this data center cooling strategy, with conditions for optimal strategy deployment.

Profiling Sustainability of Data Centers

Todays data centers consume vast amounts of energy, leading to high operational costs, excessive water consumption, and significant greenhouse gas emissions. With the approach of micro grids, an opportunity exists to reduce the environmental impact and cost of power in data centers. To realize this, demand side power consumption needs to be understood and co-managed from the perspectives of both supply and demand. We present an approach to achieve this via data center power profiling and demonstrate its applicability for an enterprise data center.

Quantifying the sustainability impact of data center availability

Data center availability is critical considering the explosive growth in Internet services and peoples dependence on them. Furthermore, in recent years, sustainability has become important. However, data center designers have little information on the sustainability impact of data center availability architectures. In this paper, we present an approach to estimate the sustainability impact of such architectures. Availability is computed using Stochastic Petri Net (SPN) models while an exergy-based lifecycle assessment (LCA) approach is used for quantifying sustainability impact. The approach is demonstrated on real life data center power infrastructure architectures. Five different architectures are considered and initial results show that quantification of sustainability impact provides important information to a data center designer in evaluating availability architecture choices.

Optimization of Global Data Center Thermal Management Workload for Minimal Environmental and Economic Burden

The rapid deployment of information and communications technology (ICT) across the globe has led to a network of high-density computer data centers to store, process and transmit information. These large-scale technology warehouses consume vast amounts of energy for running the compute infrastructure and auxiliary cooling resources. Recent literature has suggested the possibility of globally staggering compute workloads to take advantage of local climatic conditions as a means to reducing cooling energy costs. This paper further explores this premise by performing an in-depth analysis of the environmental and economic burden of managing the thermal infrastructure of a globally connected data center network. The paper examines a case study where the potential energy savings achievable by staggering workloads across arbitrarily chosen data centers in the U.S., India, and Russia are examined. The results show that the environmental benefit of such off-shoring is mostly dependent on the fuel mix of the grid to which the workload is transferred and the energy consumption in each location. Further, we show that dynamic optimization of the thermal workloads based on local weather patterns can reduce the environmental burden by up to 30%. The paper concludes with a detailed economic assessment. For the case study in this paper, we find that such global workload staggering can potentially reduce operational costs by nearly 35%.

An Exergy-Based Figure-of-Merit for Electronic Packages

Chip power consumption and heat dissipation have become important design issues because of increased energy costs and thermal management limitations. As a global compute utility evolves, seamless connectivity from the chip to the data center will become increasingly important. The optimization of such an infrastructure will require performance metrics that can adequately capture the thermodynamic and compute behavior at multiple physical length scales. In this paper, an exergy-based figure-of-merit (FoM), defined as the ratio of computing performance (in MIPS) to the thermodynamic performance (in exergy loss), is proposed for the evaluation of computational performance. The paper presents the framework to apply this metric at the chip level. Formulations for the exergy loss in simple air-cooled heat sink packages are developed, and application of the proposed approach is illustrated through two examples. The first comparatively assesses the loss in performance resulting from different cooling solutions, while the second examines the impact of non-uniformity in junction power in terms of the FoM. Modeling results on a 16 mm×24 mm chip indicate that uniform power and temperature profiles lead to minimal package irreversibility (and therefore the best thermodynamic performance). As the nonuniformity of power is increased, the performance rapidly degrades, particularly at higher power levels. Additionally, the competing needs of minimization of junction temperature and minimization of cooling power were highlighted using the exergy-based approach. It was shown that for a given power dissipation and a specific cooling architecture (such as an air-cooled heat sink solution), an optimal thermal resistance value exists beyond which the costs of increased cooling may outweigh any potential benefits in performance. Thus, the proposed FoM provides insight into thermofluidic inefficiencies that would be difficult to gain from a traditional first-law analysis. At a minimum, the framework presented in this paper enables quantitative evaluation of package performance for different nonuniform power inputs and different choices of cooling parameters. At best, since the FoM is scalable, the proposed metric has the potential to enable a chip-to-data-center strategy for optimal resource allocation.

Exergy-Based Optimization Strategies for Multi-Component Data Center Thermal Management: Part I — Analysis

As heat dissipation in data centers rises by orders of magnitude, inefficiencies such as recirculation will have an increasingly significant impact on the thermal manageability and energy efficiency of the cooling infrastructure. For example, prior work has shown that for simple data centers with a single Computer Room Air-Conditioning (CRAC) unit, an operating strategy that fails to account for inefficiencies in the air space can result in suboptimal performance. To enable system-wide optimality, an exergy-based approach to CRAC control has previously been proposed. However, application of such a strategy in a real data center environment is limited by the assumptions inherent to the single-CRAC derivation. This paper addresses these assumptions by modifying the exergy-based approach to account for the additional interactions encountered in a multi-component environment. It is shown that the modified formulation provides the framework necessary to evaluate performance of multi-component data center thermal management systems under widely different operating circumstances.Copyright