5 research outputs found

    VihreäIT metriikoiden analysointi sekä mittausviitekehyksen luonti Sonera Helsinki Datakeskus (HDC) projektille.

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    The two objectives of this thesis were to investigate and evaluate the most suitable set of energy efficiency metrics for Sonera Helsinki Data Center (HDC), and to analyze which energy efficient technologies could be implemented and in what order to gain most impact. Sustainable IT is a complex matter, and it has two components. First and the more complex matter is the energy efficiency and energy-proportionality of the IT environment. The second is the use of renewable energy sources. Both of these need to be addressed. This thesis is a theoretical study, and it focuses on energy efficiency. The use of off-site renewables is outside of the scope of this thesis. The main aim of this thesis is to improve energy efficiency through effective metric framework. In the final metric framework, metrics that target renewable energy usage in the data center are included as they are important from CO2 emission reduction perspective. The selection of energy efficient solutions in this thesis are examples from most important data center technology categories, and do not try to cover the whole array of different solutions to improve energy efficiency in a data center. The ontological goal is to present main energy efficiency metrics available in scientific discourse, and also present examples of energy efficient solutions in most energy consuming technology domains inside the data center. Even though some of the concepts are quite abstract, realism is taken into account in every analysis. The epistemology in this thesis is based on scientific articles that include empirical validation and scientific peer review. This forms the origin of the used knowledge and the nature of this knowledge. The findings from this thesis are considered valid and reliable based on the epistemology of scientific articles, and by using the actual planning documents of Sonera HDC. The reasoning in this thesis is done in abstracto, but there are many empirical results that qualify the results also as ´in concreto´. Findings are significant for Sonera HDC but they are also applicable for any general data center project or company seeking energy efficiency in their data centers.Lopputyöllä on kaksi päätavoitetta. Ensimmäinen tavoite on löytää sopivin mittausviitekehys energiatehokkuuden osoittamiseksi Sonera Helsinki Datakeskukselle (HDC). Toisena tavoitteena on analysoida, mitä energiatehokkaita ratkaisuja tulisi implementoida ja missä järjestyksessä, saavuttaakseen mahdollisimman ison vaikutuksen. Vihreä IT on monimutkainen asia ja samalla siihen liittyy kaksi eri komponenttia. Ensimmäisenä komponenttina, ja merkityksellisempänä sekä monimutkaisempana, on energiatehokkuus ja energian kulutuksen mukautuvuus suhteessa työkuormaan. Toinen komponentti vihreän IT:n osalta on uusiutuvien energialähteiden käyttäminen. Molemmat komponentit on huomioitava. Lopputyö on teoreettinen tutkimus. Lopputyön ontologinen tavoite on esittää keskeisimmät energiatehokkuusmittarit, jotka ovat saatavilla tieteellisessä keskustelussa, ja esittää myös esimerkkejä energiatehokkaista ratkaisuista teknologia-alueisiin, jotka kuluttavat eniten energiaa data keskuksissa. Vaikka osa esitetyistä ratkaisuista on melko abstraktissa todellisuudessa, realismi on pyritty ottamaan huomioon arvioita tehdessä. Epistemologisesti tämä lopputyö perustuu tieteellisiin artikkeleihin, joissa on tehty empiiristä validointia ja tiedeyhteisön vertaisarviointia tiedon totuusarvosta. Kirjoittaja pyrkii välttämään oman arvomaailman ja subjektiivisen näkemyksen tuomista analyysiin pyrkimällä enemmänkin arvioimaan ratkaisuja perustuen päätavoitteeseen, joka on sekä lisätä energiatehokkuutta että vähentää CO2 -päästöjä datakeskuksessa. Lopputyön löydökset todetaan valideiksi ja luotettaviksi, koska ne perustuvat tieteellisten artikkeleiden epistemologiaan ja siihen, että arvioinnin pohjana on käytetty todellisia Sonera HDC -projektin suunnitteludokumentteja. Päätelmät ja analyysit ovat abstrahoituja, mutta perustuvat empiirisiin tuloksiin, jotka koskevat käytännön tekemistä sekä valintoja. Löydökset ovat merkittäviä Sonera HDC -projektin kannalta, ja myös muille datakeskuksille, jotka haluavat toimia kestävän kehityksen pohjalta

    Interference of billing and scheduling strategies for energy and cost savings in modern data centers

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    The high energy consumption of HPC systems is an obstacle for evergrowing systems. Unfortunately, energy consumption does not decrease linearly with reduced workload; therefore, energy conservation techniques have been deployed on various levels which steer the overall system. While the overall saving of energy is useful, the price of energy is not necessarily proportional to the consumption. Particularly with renewable energies, there are occasions in which the price is significantly lower. The potential of saving energy costs when using smart contracts with energy providers is lacking research. In this paper, we conduct an analysis of the potential savings when applying cost-aware schedulers to data center workloads while considering power contracts that allow for dynamic (hourly) pricing. The contributions of this paper are twofold: 1) the theoretic assessment of cost savings; 2) the development of a simulator to replay batch scheduler traces which supports flexible energy cost models and various cost-aware scheduling algorithms. This allows to approximate the energy costs savings of data centers for various scenarios including off-peak and hourly budgeted energy prices as provided by the energy spot market. An evaluation is conducted with four annual job traces from the German Climate Computing Center (DKRZ) and Leibniz Supercomputing Centre (LRZ)

    Holistic Study of Thermal Management in Direct Liquid Cooled Data Centres: from the Chip to the Environment

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    The IT (Information Technology) infrastructure power consumption constitutes a large portion of global electricity consumption and a large proportion of this energy is to maintain an acceptable thermal environment for the IT equipment. Therefore, it is important to understand and improve the thermal and energy management of data centres for lower cost and higher sustainability. Toward this goal, Direct Contact Liquid Cooled (DCLC) servers, where liquid loop heat exchangers are attached to the CPU, were proposed to study the use of chiller-less energy efficient data centre. Thirty Sun Fire V20z servers in a data centre rack have their CPUs water cooled with the remaining components air cooled, together with a rear door heat exchanger to capture this air heat flow. The heat generated by the servers is ultimately transferred to the environment using an Air Handling Unit (AHU). The AHU was fitted with a water spray system to increase the heat transfer capacity. The designed DCLC system was tested and characterised in terms of power consumption and thermal performance. The design successfully provided stable inlet coolant temperature (±1℃) to the IT despite the variation in the IT workload and environmental conditions. Activating the spray reduced the thermal resistance of the AHU heat exchanger (HE) by 50%. However, the power consumption and pressure drop across the HE was increased. The flow distribution and the coolant pumping configurations of centralised (where the coolant is pumped by two central pumps connected in series) and distributed (where small pumps inside the servers are activated) was investigated. The EPANET software was used to analyse the flow and showed that the servers in the top of the rack receive a higher flow rate (by approximately 30%) than the servers in the bottom of the rack. This resulted in a variation in the CPU temperatures of different servers. Optimisation analysis proposed increasing the manifolds size to improve the flow rate and reduce the flow maldistribution. In the distributed pumping case, the CPUs temperature showed to be 2℃ higher compared with the central pumping case for the high IT workload. The rack inlet temperature was tested in the range of the ASHRAE W4 envelope in terms of CPU temperatures, power consumption and computational efficiency. Increasing the coolant inlet temperature resulted in high energy saving in the AHU, while the rack energy consumption increases marginally in idle operation and considerably more in high IT workloads. This results in an improvement in the energy effectiveness of 17% but a deterioration in the computational efficiency of 4%. Finally, a parallel study was carried out to investigate the droplet evaporation over heated surfaces which ultimately be used in studying sprays in the AHU or in direct on chip cooling via evaporation. A novel experimental design was proposed to track the lifetime of any droplet size that span the surface tension to gravitydominated regimes. A theoretical model was also proposed to predict the droplet lifetime based on the initial contact angle, contact radius and the receding contact angle. The model predicted the droplet evaporation over hydrophobic surfaces with good accuracy of an error less than 4% while under estimated the evaporation with hydrophilic surfaces

    Contemporary analysis and architecture for a generic cloud-based sensor data management platform.

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    An increasing volume of data is being generated by sensors and smart devices deployed in different areas, often far from computing facilities such as data centres. These data can be difficult to gather and process using local computing infrastructure. This is due to cost and limited resources. Cloud computing provides scalable resources that are capable of addressing such problems. However, platform-independent methods of gathering and transmitting sensor data to Clouds are not widely available. This paper presents a state-of-the-art analysis of Cloud-based sensor monitoring and data gathering platforms. It discusses their strengths and weaknesses and reviews the current trends in this area. Informed by the analysis, the paper further proposes a generic conceptual architecture for achieving a platform-neutral Cloud-based sensor monitoring and data gathering platform. We also discuss the objectives, design decisions and the implementation considerations for the conceptual architecture.IC

    A reference model for integrated energy and power management of HPC systems

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    Optimizing a computer for highest performance dictates the efficient use of its limited resources. Computers as a whole are rather complex. Therefore, it is not sufficient to consider optimizing hardware and software components independently. Instead, a holistic view to manage the interactions of all components is essential to achieve system-wide efficiency. For High Performance Computing (HPC) systems, today, the major limiting resources are energy and power. The hardware mechanisms to measure and control energy and power are exposed to software. The software systems using these mechanisms range from firmware, operating system, system software to tools and applications. Efforts to improve energy and power efficiency of HPC systems and the infrastructure of HPC centers achieve perpetual advances. In isolation, these efforts are unable to cope with the rising energy and power demands of large scale systems. A systematic way to integrate multiple optimization strategies, which build on complementary, interacting hardware and software systems is missing. This work provides a reference model for integrated energy and power management of HPC systems: the Open Integrated Energy and Power (OIEP) reference model. The goal is to enable the implementation, setup, and maintenance of modular system-wide energy and power management solutions. The proposed model goes beyond current practices, which focus on individual HPC centers or implementations, in that it allows to universally describe any hierarchical energy and power management systems with a multitude of requirements. The model builds solid foundations to be understandable and verifiable, to guarantee stable interaction of hardware and software components, for a known and trusted chain of command. This work identifies the main building blocks of the OIEP reference model, describes their abstract setup, and shows concrete instances thereof. A principal aspect is how the individual components are connected, interface in a hierarchical manner and thus can optimize for the global policy, pursued as a computing center's operating strategy. In addition to the reference model itself, a method for applying the reference model is presented. This method is used to show the practicality of the reference model and its application. For future research in energy and power management of HPC systems, the OIEP reference model forms a cornerstone to realize --- plan, develop and integrate --- innovative energy and power management solutions. For HPC systems themselves, it supports to transparently manage current systems with their inherent complexity, it allows to integrate novel solutions into existing setups, and it enables to design new systems from scratch. In fact, the OIEP reference model represents a basis for holistic efficient optimization.Computer auf höchstmögliche Rechenleistung zu optimieren bedingt Effizienzmaximierung aller limitierenden Ressourcen. Computer sind komplexe Systeme. Deshalb ist es nicht ausreichend, Hardware und Software isoliert zu betrachten. Stattdessen ist eine Gesamtsicht des Systems notwendig, um die Interaktionen aller Einzelkomponenten zu organisieren und systemweite Optimierungen zu ermöglichen. Für Höchstleistungsrechner (HLR) ist die limitierende Ressource heute ihre Leistungsaufnahme und der resultierende Gesamtenergieverbrauch. In aktuellen HLR-Systemen sind Energie- und Leistungsaufnahme programmatisch auslesbar als auch direkt und indirekt steuerbar. Diese Mechanismen werden in diversen Softwarekomponenten von Firmware, Betriebssystem, Systemsoftware bis hin zu Werkzeugen und Anwendungen genutzt und stetig weiterentwickelt. Durch die Komplexität der interagierenden Systeme ist eine systematische Optimierung des Gesamtsystems nur schwer durchführbar, als auch nachvollziehbar. Ein methodisches Vorgehen zur Integration verschiedener Optimierungsansätze, die auf komplementäre, interagierende Hardware- und Softwaresysteme aufbauen, fehlt. Diese Arbeit beschreibt ein Referenzmodell für integriertes Energie- und Leistungsmanagement von HLR-Systemen, das „Open Integrated Energy and Power (OIEP)“ Referenzmodell. Das Ziel ist ein Referenzmodell, dass die Entwicklung von modularen, systemweiten energie- und leistungsoptimierenden Sofware-Verbunden ermöglicht und diese als allgemeines hierarchisches Managementsystem beschreibt. Dies hebt das Modell von bisherigen Ansätzen ab, welche sich auf Einzellösungen, spezifischen Software oder die Bedürfnisse einzelner Rechenzentren beschränken. Dazu beschreibt es Grundlagen für ein planbares und verifizierbares Gesamtsystem und erlaubt nachvollziehbares und sicheres Delegieren von Energie- und Leistungsmanagement an Untersysteme unter Aufrechterhaltung der Befehlskette. Die Arbeit liefert die Grundlagen des Referenzmodells. Hierbei werden die Einzelkomponenten der Software-Verbunde identifiziert, deren abstrakter Aufbau sowie konkrete Instanziierungen gezeigt. Spezielles Augenmerk liegt auf dem hierarchischen Aufbau und der resultierenden Interaktionen der Komponenten. Die allgemeine Beschreibung des Referenzmodells erlaubt den Entwurf von Systemarchitekturen, welche letztendlich die Effizienzmaximierung der Ressource Energie mit den gegebenen Mechanismen ganzheitlich umsetzen können. Hierfür wird ein Verfahren zur methodischen Anwendung des Referenzmodells beschrieben, welches die Modellierung beliebiger Energie- und Leistungsverwaltungssystemen ermöglicht. Für Forschung im Bereich des Energie- und Leistungsmanagement für HLR bildet das OIEP Referenzmodell Eckstein, um Planung, Entwicklung und Integration von innovativen Lösungen umzusetzen. Für die HLR-Systeme selbst unterstützt es nachvollziehbare Verwaltung der komplexen Systeme und bietet die Möglichkeit, neue Beschaffungen und Entwicklungen erfolgreich zu integrieren. Das OIEP Referenzmodell bietet somit ein Fundament für gesamtheitliche effiziente Systemoptimierung
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