data-intensive computations
Big provenance stream processing for data-intensive computations
... Big Data processing workflow management tools which support chained ...the data lifecycle in Hadoop Big Data ...creating data processing pipelines by connecting Hadoop based processing ...of ...
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Scalable Parallel Computing on Clouds : Efficient and scalable architectures to perform pleasingly parallel, MapReduce and iterative data intensive computations on cloud environments
... Conclusions • Highly available, scalable decentralized iterative MapReduce architecture on eventual consistent services • More natural Iterative programming model extensions to MapReduce[r] ...
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SCALABLE PARALLEL COMPUTING ON CLOUDS: EFFICIENT AND SCALABLE ARCHITECTURES TO PERFORM PLEASINGLY PARALLEL, MAPREDUCE AND ITERATIVE DATA INTENSIVE COMPUTATIONS ON CLOUD ENVIRONMENTS
... cloud data centers, combined with the comparable performance reported here, suggests that loosely‐coupled science applications will be increasingly implemented on clouds, and that using MapReduce frameworks will ...
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Data Management in Data Intensive Computing Systems - A Survey
... in data intensive computing, it is important to minimize the movement of ...data. Data intensive computing uses distributed data and distributed file systems (DFS) in which the ...
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Cloud Technologies and Data Intensive Applications
... • Traditional Supercomputers TeraGrid and DEISA for large scale parallel computing – mainly simulations – Likely to offer major GPU enhanced systems • Traditional Grids for handling dist[r] ...
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Geoinformatics and Data Intensive Applications on Clouds
... • Broad Overview: Trends from Data Deluge to Clouds • Clouds, Grids and Supercomputers: Infrastructure and Applications that work on clouds • MapReduce and Iterative MapReduce for non tr[r] ...
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FutureGrid and Data Intensive Applications on Clouds
... DPFS Data Parallel File System: Support of file systems like Google (MapReduce), HDFS (Hadoop) or Cosmos (dryad) with compute-data affinity optimized for data processing Table: Support of Table ...
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Clouds for Sensors and Data Intensive Applications
... • Large Scale Supercomputers – Multicore nodes linked by high performance low latency network – Increasingly with GPU enhancement – Suitable for highly parallel simulations • High Throug[r] ...
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Data Intensive Clouds Tools and Applications
... Data We’re Looking at • Biology DNA sequence alignments Medical School & CGB several million Sequences / at least 300 to 400 base pair each • Particle physics LHC Caltech 1 Terabyte data[r] ...
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Data classification algorithm for data intensive computing environments
... big data, mining useful infor- mation has become a subject of interest. Data-intensive environments have been considered only in the context of big data mining ...on data mining ...
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Syntactic Approaches to Automatic Book Indexing
... negative dictionary quantitative computations recall computations* relevance values* retrieval system T subset implemented system computations system implemented system operations term-d[r] ...
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Data Intensive Biomedical Computing Systems
... Calculate pairwise distances for a collection of genes used for clustering, MDS ON^2 problem “Doubly Data Parallel” at Dryad Stage Performance close to MPI Performed on 768 cores Tempest[r] ...
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To Overlap or Not to Overlap: Optimizing Incremental MapReduce Computations for On-Demand Data Upload
... the data to be uploaded is a multiple of wave size, for the vast major- ity of cases this does not ...less data means less wait time in the beginning, that cannot be overlapped with the com- ...the ...
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Data Intensive Biomedical Computing Systems
... Calculate pairwise distances for a collection of genes used for clustering, MDS ON^2 problem “Doubly Data Parallel” at Dryad Stage Performance close to MPI Performed on 768 cores Tempest[r] ...
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A Simulator for Data-Intensive Job Scheduling
... Work Conservation We assume that the running time of a job’s tasks is not influenced by the time or choice of task slot it is run onto. In particular, this means that each job will require the same amount of total ...
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Cloud Technologies for Data Intensive Computing
... Calculate pairwise distances for a collection of genes used for clustering, MDS ON^2 problem “Doubly Data Parallel” at Dryad Stage Performance close to MPI Performed on 768 cores Tempest[r] ...
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Delegating RAM Computations
... More on the analysis of KRR. We describe the argument of [KRR14] and explain why it fails for non-deterministic computations. To go from local satisfiability to full-fledged satisfiability, the proof of [KRR14] ...
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COMPUTATIONS IN DEA. Abstract
... entire data set are almost the ...the data for the four models will require roughly three times the time to find the frame of the variable returns ...“dense” data sets do not seem to be the ...DEA ...
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A calculus for costed computations
... In order to obtain our more abstract wLTS we forget some of the details in the labels of the actions of the operational semantics for Picost, given in Figure 6 and Figure 7, so that they[r] ...
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MapReduce for Data Intensive Scientific Analyses
... “MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate ...
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