Titlebook: Euro-Par 2017: Parallel Processing; 23rd International C Francisco F. Rivera,Tomás F. Pena,José C. Cabaleir Conference proceedings 2017 Spr

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Shutdown Policies with Power Capping for?Large Scale Computing Systems of the system. In this paper, we propose models translating these various constraints into different shutdown policies that can be combined. Our models are validated through simulations on real workload traces and power measurements on real testbeds.

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Conference proceedings 2017uted data management and analytics; cluster and cloud computing; distributed systems and algorithms;?parallel and distributed programming, interfaces and languages; multicore and manycore parallelism; theory and algorithms for parallel computation and networking; prallel numerical methods and applications; and accelerator?computing.

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https://doi.org/10.1007/978-3-662-42975-4enecks on NUMA systems. Our in-depth evaluation reveals that the optimal partitioning strategy depends on a variety of factors and consequently, we derive a set of indicators for selecting the optimal partitioning strategy suitable for a given graph and workload.

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Off-Road Performance Modeling – How to Deal with Segmented Data paper, we present an algorithm to detect segmentation in a sequence of performance measurements and estimate the point where the behavior changes. Our method correctly identified segmentation in more than 80% of 5.2 million synthetic tests and confirmed expected segmentation in three application case studies.

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Performance Characterization of De Novo Genome Assembly on Leading Parallel Systems enough problems, it also demonstrates excellent scaling across nodes in an HPC system, but requires a high speed network with low overhead and high injection rates. Our results shed light on the architectural features that are most important for achieving good parallel efficiency on this and related problems.

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Partitioning Strategy Selection for In-Memory Graph Pattern Matching on Multiprocessor Systemsenecks on NUMA systems. Our in-depth evaluation reveals that the optimal partitioning strategy depends on a variety of factors and consequently, we derive a set of indicators for selecting the optimal partitioning strategy suitable for a given graph and workload.