Chapter Globally Optimised Energy-Efficient Data Centres

A great deal of energy in Information and Communication Technology (ICT) systems can be wasted by software, regardless of how energy-efficient the underlying hardware is. To avoid such waste, programmers need to understand the energy consumption of programs during the development process rather than waiting to measure energy after deployment. Such understanding is hindered by the large conceptual gap from hardware, where energy is consumed, to high-level languages and programming abstractions. The approaches described in this chapter involve two main topics: energy modelling and energy analysis. The purpose of modelling is to attribute energy values to programming constructs, whether at the level of machine instructions, intermediate code or source code. Energy analysis involves inferring the energy consumption of a program from the program semantics along with an energy model. Finally, the chapter discusses how energy analysis and modelling techniques can be incorporated in software engineering tools, including existing compilers, to assist the energy-aware programmer to optimise the energy consumption of code

Implementation and demonstration of a building simulation based testbed for assessment of data centre multi-domain control strategies

The traditional data centre (DC) infrastructure is being\u3cbr/\u3esignificantly extended by modern information technology\u3cbr/\u3e(IT) trends on one side, and lasting calling for DC\u3cbr/\u3esustainability on the other. A holistic DC management\u3cbr/\u3ewill be necessary to coordinate different DC processes\u3cbr/\u3eand to dock the DC environment into modern cities and\u3cbr/\u3edistrict infrastructure. A development of such a complex\u3cbr/\u3emanagement requires comprehensive testing possibilities.\u3cbr/\u3eThe testing is hardly possible on the real DC infrastructure\u3cbr/\u3edue to the mission critical nature. Building energy\u3cbr/\u3emodelling methods offer a suitable platform for the\u3cbr/\u3edevelopment of a safe and reliable testing environment.\u3cbr/\u3eThis paper deals with new application of Building Energy\u3cbr/\u3eSimulation (BES) method and introduces a workflow for\u3cbr/\u3evirtual closed-loop testing of enhanced multi-domain\u3cbr/\u3eoperation for data centres\u3cbr/\u3

Simulation-based assessment of thermal aware computation of a bespoke data centre

The role of Data Centres (DCs) as global electricity consumers is growing rapidly due to the exponential increase of computational demand that modern times require. Control strategies that minimize energy consumption while guaranteeing optimal operation conditions in DC are essential to achieve sustainable and energy efficient DCs. Unfortunately, the development and testing of novel control strategies are often slowed down, if not discarded. This is generally due to the lack of access caused by safety and economic reasons. Alternatively, simulation experiments represent a “safe” virtual environment to test novel control strategies, accelerating the process for their implementation in physical DCs. The virtual DC testbed, originated in the GENiC project, supports the development and dynamic testing of control and energy management algorithms. This paper introduces its features and describes its functionality through a simulation-based assessment of thermal aware computation strategy. For this, the virtual DC will be based on a bespoke DC located in Cork (Ireland). This DC has 30 kW capacity, 40 m2 floor area and its layout follows a hot aisle - cold aisle arrangement without containment. The performance the IT Workload allocation under different scenarios and their influence both on the whitespace environment and overall DC performance are evaluated and quantified. Finally, the benefits of a coordinated operation between the thermal and the IT workload managements are discussed

ICT - Energy Concepts for Energy Efficiency and Sustainability

Data centres are part of today's critical information and communication infrastructure, and the majority of business transactions as well as much of our digital life now depend on them. At the same time, data centres are large primary energy consumers, with energy consumed by IT and server room air conditioning equipment and also by general building facilities. In many data centres, IT equipment energy and cooling energy requirements are not always coordinated, so energy consumption is not optimised. Most data centres lack an integrated energy management system that jointly optimises and controls all its energy consuming equipments in order to reduce energy consumption and increase the usage of local renewable energy sources. In this chapter, the authors discuss the challenges of coordinated energy management in data centres and present a novel scalable, integrated energy management system architecture for data centre wide optimisation. A prototype of the system has been implemented, including joint workload and thermal management algorithms. The control algorithms are evaluated in an accurate simulation‐based model of a real data centre. Results show significant energy savings potential, in some cases up to 40%, by integrating workload and thermal management

Chapter Globally Optimised Energy-Efficient Data Centres

A great deal of energy in Information and Communication Technology (ICT) systems can be wasted by software, regardless of how energy-efficient the underlying hardware is. To avoid such waste, programmers need to understand the energy consumption of programs during the development process rather than waiting to measure energy after deployment. Such understanding is hindered by the large conceptual gap from hardware, where energy is consumed, to high-level languages and programming abstractions. The approaches described in this chapter involve two main topics: energy modelling and energy analysis. The purpose of modelling is to attribute energy values to programming constructs, whether at the level of machine instructions, intermediate code or source code. Energy analysis involves inferring the energy consumption of a program from the program semantics along with an energy model. Finally, the chapter discusses how energy analysis and modelling techniques can be incorporated in software engineering tools, including existing compilers, to assist the energy-aware programmer to optimise the energy consumption of code