Operating policies for energy efficient large scale computing

PhD ThesisEnergy costs now dominate IT infrastructure total cost of ownership, with datacentre operators predicted to spend more on energy than hardware infrastructure in the next five years. With Western European datacentre power consumption estimated at 56 TWh/year in 2007 and projected to double by 2020, improvements in energy efficiency of IT operations is imperative. The issue is further compounded by social and political factors and strict environmental legislation governing organisations. One such example of large IT systems includes high-throughput cycle stealing distributed systems such as HTCondor and BOINC, which allow organisations to leverage spare capacity on existing infrastructure to undertake valuable computation. As a consequence of increased scrutiny of the energy impact of these systems, aggressive power management policies are often employed to reduce the energy impact of institutional clusters, but in doing so these policies severely restrict the computational resources available for high-throughput systems. These policies are often configured to quickly transition servers and end-user cluster machines into low power states after only short idle periods, further compounding the issue of reliability. In this thesis, we evaluate operating policies for energy efficiency in large-scale computing environments by means of trace-driven discrete event simulation, leveraging real-world workload traces collected within Newcastle University. The major contributions of this thesis are as follows: i) Evaluation of novel energy efficient management policies for a decentralised peer-to-peer (P2P) BitTorrent environment. ii) Introduce a novel simulation environment for the evaluation of energy efficiency of large scale high-throughput computing systems, and propose a generalisable model of energy consumption in high-throughput computing systems. iii iii) Proposal and evaluation of resource allocation strategies for energy consumption in high-throughput computing systems for a real workload. iv) Proposal and evaluation for a realworkload ofmechanisms to reduce wasted task execution within high-throughput computing systems to reduce energy consumption. v) Evaluation of the impact of fault tolerance mechanisms on energy consumption

Caracterização computacional para alocação distribuída para uma configuração com interface natural de usuário

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2015.Em um sistema distribuído heterogêneo, como grades computacionais, a escolha do sistema computacional para processar uma tarefa é realizada por meio de heurísticas adotadas igualmente para todos os sistemas. Os métodos atuais para avaliação da carga computacional, em grades heterogêneas, não levam em consideração características qualitativas que afetam o desempenho. Sistemas computacionais aparentemente idênticos, com as mesmas características quantitativas (tal como a quantidade de núcleos de processamento e de memória), podem apresentar desempenhos desiguais. O método proposto consiste em uma política de informação ao balanceamento de carga e tem como objetivo mensurar a carga dos sistemas computacionais por meio da avaliação de seus recursos quantitativos, tanto os imutáveis (como a quantidade de núcleos de processamento) quanto os mutáveis (como o percentual de memória livre), e qualitativos, inerentes à arquitetura do sistema computacional. A comparação da carga computacional entre os sistemas permite que o balanceamento de carga seja realizado mesmo em sistemas distribuídos heterogêneos para que seja possível a escolha do sistema computacional no qual executar uma tarefa da forma mais eficiente. Esta pesquisa utiliza a ferramenta CVFlow, uma Interface Natural de Usuário destinada ao balanceamento de carga, para avaliar o método proposto. O experimento consiste no escalonamento de um conjunto de tarefas e na comparação do método proposto com o estado da arte presente na literatura. O método proposto fornece um conjunto de melhorias que distribuem a carga de forma mais homogênea entre os sistemas computacionais, evitando, assim, sobrecarregar um sistema específico, além de oferecer um desempenho superior na execução do conjunto de tarefas.Abstract : In a distributed heterogeneous system, such as grids, the choice of a computer system to process a task is performed by means of heuristics adopted equally for all systems. Current methods for assessing the computing load, on heterogeneous grids, do not take into account qualitative characteristics that affect performance. Computer systems apparently identical, with the same quantitative traits (such as the number of processing cores and memory), may provide different performance. The proposed method consists of an information policy to load balancing. It aims to measure the load of a computer systems through the assessment of their quantitative and qualitative features. Quantitative, both immutable (as the number of cores) and mutable (as the percentage of free memory). And the qualitative, inherent to the computer system architecture. Comparison of computational load between systems allows load balancing to be performed even in heterogeneous distributed systems, to be able to choose the computer system on which to perform a task more efficiently. This research uses the CVFlow tool, a Natural User Interface intended for load balancing, to evaluate the proposed method. The experiment consists of the scheduling of a set of tasks and the comparison of the proposed method with the state of the art. The proposed method provides a set of improvements that distribute the load more evenly among computer systems, avoid overloading a particular system, and provides a better performance on the execution of the set of tasks