the world of big data is in need of high levels of scalability and the question, how to effectively process large-scale data sets is becoming increasingly relevant. Furthermore the existing data management schemes do ...
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Pattern matching is an important operation in various applications such as computer and network security, bioinformatics, image processing, among many others. Aho-Corasick (AC) algorithm is a multiple patterns matchin...
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Context-aware computing is a new paradigm that relies on large amounts of data collected from a variety of sources, ranging from smartphones to sensors, to automatically take smart decisions. this usually leads to lar...
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Dynamic programming approach solves complex problems efficiently by breaking them down into simpler sub-problems, and is widely utilized in scientific computing. Withthe increasing data volume of scientific applicati...
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Sharing the Semantic Web data in proprietary datasets in which data is encoded in RDF triples in a decentralized environment calls for efficient support from distributed computing technologies. the highly dynamic ad-h...
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Current performance analysis and tuning tools must be able to improve the performance of large-scale parallel applications. To be effective, such analysis and tuning tools must be scalable and be able to manage the dy...
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We investigate models that efficiently map branch-And-bound algorithms on a distributed computer architecture using a case of multidimensional Lipschitz Global Optimization. A combination of MPI and Pthreads is studie...
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the necessity for capping carbon emission has significantly restricted the potential of modern data centers. For this matter, both industry and academia are proactively seeking opportunities on cross-layer power manag...
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ISBN:
(纸本)9781467355872
the necessity for capping carbon emission has significantly restricted the potential of modern data centers. For this matter, both industry and academia are proactively seeking opportunities on cross-layer power management schemes that could open a door for sustainable high-performance computing platform. In this paper we investigate an emerging trend in the IT industry: using promising onsite distributed generation (DG) techniques to provide premium clean energy to the computing load. We develop data center power demand shaping (PDS), a novel technique that allows data centers to utilize onsite green energy efficiently. In contrast to prior design, PDS takes advantage of a so-far unexplored power supply feature, i.e., the load following capabilities of DG systems to avoid the high performance penalty issue incurred during supply tracking. In addition, PDS features two adaptive power management schemes: DGR Boost and UPS Boost. these two workload-aware optimization methods leverage mature computer tuning knobs to achieve attractive data center performance improvement. Using real-world data center traces and industry data of distributed generation systems, we show that our technique can come within 1.2% performance of an ideal oracle, which is roughly a 37% improvement over existing supply tracking based design. Our design could save over 100 metric tons of carbon emissions annually for a 10MW data center.
In our paper we present an abstract object oriented runtime system that helps to develop scientific applications for new her erogenous architectures based on multi-node of multi-core processors enhanced with accelerat...
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Standard system tools employed by users on a daily basis do not take full advantage of parallel file system I/O bandwidth and do not understand associated idiosyncrasies such as Lustre striping. this can lead ton on-o...
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