Titlebook: Euro-Par 2014: Parallel Processing; 20th International C Fernando Silva,Inês Dutra,Vítor Santos Costa Conference proceedings 2014 Springer

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DReAM: Per-Task DRAM Energy Metering in Multicore Systems multicores, which opens new paths to energy/performance optimizations, such as per-task energy-aware task scheduling and energy-aware billing in datacenters. In particular, the contributions of this paper are (i) an ideal per-task energy metering model for DRAM memories; (ii) ., an accurate, yet lo

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Characterizing the Performance-Energy Tradeoff of Small ARM Cores in HPC ComputationThe ARM platform that dominates the embedded and mobile computing segments is now being considered as an alternative to high-end x86 processors that largely dominate HPC because peak performance per watt may be substantially improved using off-the-shelf commodity processors..In this work we methodic

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On Interactions among Scheduling Policies: Finding Efficient Queue Setup Using High-Resolution Simulthms have been proposed for systems with specific requirements, mainstream resource management systems and schedulers are still only using a limited set of scheduling policies. Production systems need to balance various policies that are set in place to satisfy both the resource providers and users

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A Queueing Theory Approach to Pareto Optimal Bags-of-Tasks Scheduling on Clouds this scalability also becomes limited. To investigate the impact of this limitation we focus on bags–of–tasks where task data is stored outside the cloud and has to be transferred across the network before task execution can commence. The existing bags–of–tasks estimation tools are not able to prov

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SPAGHETtI: Scheduling/Placement Approach for Task-Graphs on HETerogeneous archItecture architecture (e.g. CPU or GPU). We show that this algorithm is optimal in complexity .(|.||.|. + |.||.|), where |.| is the number of edges, |.| the number of vertices of the scheduled DAG and |.| the number of architectures – usually a small value – and that it is able to compute the optimal makesp

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Energy-Aware Multi-Organization Scheduling Problemove machine utilization; however, this can also increase operational costs of less-loaded organizations..We consider energy as a resource, where the objective is to optimize the total energy consumption without increasing the energy spent by a .. We model the problem as a energy-aware variant of the

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