Rocky Shih

Data analysis, visualization and knowledge discovery in sustainable data centers

A significant amount of energy consumption is now attributed to data centers due to their ever increasing numbers, size and power densities. Thus, there are efforts focused at making a data center more sustainable by reducing its energy consumption and carbon footprint. This requires an end-to-end management approach with requirements derived from service level agreements (SLAs) and a flexible infrastructure that can be closely monitored and finely controlled. The infrastructure can then be manipulated to satisfy the requirements while optimizing for sustainability metrics and total cost of operations. In this paper, we explore the role of data analysis, visualization and knowledge discovery techniques in improving the sustainability of a data center. We present use cases from a large, sensor-rich, state-of-the-art data center on the application of these techniques to the three main sub-systems of a data center, namely, power, cooling and compute. Furthermore, we provide recommendations for where these techniques can be used within these sub-systems for improving sustainability metrics of a data center.

Optimization and control of cooling microgrids for data centers

Reliable operation of todays data centers requires a tremendous amount of electricity to power both the IT equipment and the supporting cooling facilities. As much as half of total data center electricity consumption can be attributed to the cooling systems required to maintain the thermal status of IT equipment. In order to lower the electricity usage of the cooling system and hence reduce the data center environmental footprint, alternative cooling resources, such as water and air-side economizers, are being exploited to supplement or replace the traditional chilled water based cooling schemes. The various cooling resource options, together with the mechanisms to distribute and deliver the cooling resource to IT equipment racks, constitute a cooling microgrid. In this paper, we present a holistic perspective for the optimization and control of the data center cooling microgrid. The holistic approach optimizes the sourcing and distribution of cooling resources from the site portfolio in response to real-time weather changes and site demand. The cooling microgrid optimization and control framework has been implemented in a research data center; we estimate that the framework cuts the yearly cooling costs by 30%.

Kratos: Automated Management of Cooling Capacity in Data Centers With Adaptive Vent Tiles

In data centers with raised floor architecture, the floor tiles are typically perforated, delivering the cold air from the plenum to the inlets of equipment located in racks. The environment of these data centers is dynamic in that the workload and power dissipation fluctuate considerably over both short-term and long-term time scales. As such, airflow requirements vary continuously. However, due to labor costs and lack of expertise, the tiles are adjusted infrequently, and many data centers are grossly over provisioned for airflow in general and/or lack sufficient airflow delivery in certain local areas. This wastes energy and reduces data center thermal capacity. We have previously introduced Kratos, an Adaptive Vent Tile (AVT) technology that addresses this problem by automatically adjusting mechanical louvers mounted to the tiles in response to the needs of nearby IT equipment. Our initial results were limited to a 3-tile test bed that allowed us to prove concept but did not provide for scalability. This paper extends the previous work by expanding the size of the test bed to 28 tiles and 29 racks located in multiple thermal zones. We present experimental modeling results on the MIMO (Multi-Input Multi-Output) system and provide insights on the external behavior of the system through CFD (Computational Fluid Dynamic) analysis. We develop an MPC (Model-based Predictive Control) controller to maintain the temperatures of racks below the thresholds through vent tile tuning. Experimental results show that the controller can maintain the temperature below the thresholds while reducing overall cooling air requirements.Copyright

LIFECYCLE-BASED DATA CENTER DESIGN

Environmental sustainability is an increasingly important design constraint for next-generation servers and datacenters. Unlike prior studies that focus on operational energy use, we study the environmental impact of current designs across the entire lifecycle, including embedded impact factors related to material use and manufacturing. Based on the insights provided by this study, we propose a solution co-designed across system architecture and physical packaging, including (1) material-efficient physical organization, (2) environmentally-efficient cooling infrastructures, and (3) effective design of system architectures to reuse components — all working together to improve sustainability. We provide a detailed evaluation of our proposed solution in terms of sustainability, thermal manageability, and computational performance. Our results show that the proposed approach is effective in addressing the (often non-intuitive) tradeoffs between performance and different components of sustainability.Copyright

Totally green: evaluating and designing servers for lifecycle environmental impact

The environmental impact of servers and datacenters is an important future challenge. System architects have traditionally focused on operational energy as a proxy for designing green servers, but this ignores important environmental implications from server production (materials, manufacturing, etc.). In contrast, this paper argues for a lifecycle focus on the environmental impact of future server designs, to include both operation and production. We present a new methodology to quantify the total environmental impact of system design decisions. Our approach uses the thermodynamic metric of exergy consumption, adapted and validated for use by system architects. Using this methodology, we evaluate the lifecycle impact of several example system designs with environment-friendly optimizations. Our results show that environmental impact from production can be important (around 20% on current servers and growing) and system design choices can reduce this component (by 30--40%). Our results also highlight several, sometimes unexpected, cross-interactions between the environmental impact of production and operation that further motivate a total lifecycle emphasis for future green server designs.

Integrated management of cooling resources in air-cooled data centers

To accommodate the dynamic environment within raised floor data centers, cooling capacity is tuned during operation through zonal control means, e.g., active management of air conditioning resources. However, due to the spatial variance of cooling efficiency and time-varying cooling demand within zones, zonal adjustments alone are not able to maximize the thermal capacity of data centers. Without making local adjustments to the physical structure, such as altering vent tile openings, a data center can suffer significant reduction in thermal capacity and cooling efficiency, and such that facility lifespan. In this paper, we present active cooling technologies using both local and zonal actuators that improve overall cooling efficiency. Experimental evaluation in a data center shows that the integrated controller can adapt to changes to the system under control, significantly improve the controllability of the temperatures and reduce the energy consumption of the cooling facility.

Optimization of Outside Air Cooling in Data Centers

Airside economizers in data centers introducing outside air directly in cold aisles or at CRAC level have been considered recently to reduce overall energy to cool IT equipment. However, such designs limit the operational envelope of free cooling based on the required supply air temperature to the IT equipment. More studies are required to optimize airside economizer layouts to increase the operation time and hence, increase the energy savings. This paper presents a case study of different outside air delivery configurations including outside air introduced in cold aisles, in plenum close to CRAC units’ supply side, at return side of CRAC units and in hot aisles. The temperature and flow fields are studied numerically and are compared to each other. Mixing of the cooler outside air with the hot air is studied to determine optimal local distribution of the outside air in a non-homogeneous data center to maximize natural cooling. The paper also quantifies the annual average performance of the outside air infrastructure to include the effects of the seasonal variations in the ambient temperature.Copyright

Application of Exploratory Data Analysis (EDA) Techniques to Temperature Data in a Conventional Data Center

Data centers are the computational hub of the next generation. Rise in demand for computing has driven the emergence of high density datacenters. With the advent of high density, mission-critical datacenters, demand for electrical power for compute and cooling has grown. Deployment of a large number of high powered computer systems in very dense configurations in racks within data centers will result in very high power densities at room level. Hosting business and mission-critical applications also demand a high degree of reliability and flexibility. Managing such high power levels in the data center with cost effective reliable cooling solutions is essential to feasibility of pervasive compute infrastructure. Energy consumption of data centers can also be severely increased by over-designed air handling systems and rack layouts that allow the hot and cold air streams to mix. Absence of rack level temperature monitoring has contributed to lack of knowledge of air flow patterns and thermal management issues in conventional data centers. In this paper, we present results from exploratory data analysis (EDA) of rack-level temperature data collected over a period of several months from a conventional production datacenter. Typical datacenters experience surges in power consumption due to rise and fall in compute demand. These surges can be long term, short term or periodic, leading to associated thermal management challenges. Some variations may also be machine-dependent and vary across the datacenter. Yet other thermal perturbations may be localized and momentary. Random variations due to sensor response and calibration, if not identified, may lead to erroneous conclusions and expensive faults. Among other indicators, EDA techniques also reveal relationships among sensors and deployed hardware in space and time. Identification of such patterns can provide significant insight into data center dynamics for future forecasting purposes. Knowledge of such metrics enables energy-efficient thermal management by helping to create strategies for normal operation and disaster recovery for use with techniques like dynamic smart cooling.Copyright

Air cooling limits of 3D stacked logic processor and memory dies

Through-Silicon-Vias (TSVs) enable 3D stack of logic processor and memory dies with significant improvement in latency and energy efficiency of large memory-bound computations. However, additional layers of memory die increase IC package thermal resistance. Thermal management has been identified as a key challenge to achieve high computation power and memory density in the same package. In this paper we present a numerical study on temperature mapping of 3D stacked dies in air-cooled package. We consider DRAM based memory with low power, mid power, and high power logic processors. We study the effect of logic processor power and number of memory dies on the temperature profile. This study provides thermally viable design space of compute-power to memory-size.

Automated synthesis of sustainable data centers

Next generation data centers must be designed to meet Service Level Agreements (SLAs) for application performance while reducing costs and environmental impact. Traditional design approaches are manually intensive and must integrate thousands of components at multiple granularities, often with conflicting goals. We propose an Automated Data Center Synthesizer to design Sustainable Data Centers that meet SLA goals, minimize carbon emissions and embedded exergy, are optimally efficient and deliver significantly reduced Total Cost of Ownership (TCO). The paper concludes with a use case study that employs the synthesizer process flow to design an optimal data center to deliver a set of services for a hypothetical city using state of the art sustainable technologies.