Data Intensive
Matching Data Intensive Applications and Hardware/Software Architectures
... big data applications to identify characteristics of data intensive applications and propose a big data version of the famous Berkeley dwarfs and NAS parallel ...
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LATEST DATA STORAGE TECHNIQUES IN CLOUD COMPUTING FOR DATA INTENSIVE APPLICATIONS
... many data intensive cloud ...is data replication that brings data nearer to data intensive ...high data availability. In this paper we study data replication ...
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Map Reduce for Data Intensive Scientific Analyses
... textual data processing using Hadoop, we could not find any schemes for using MapReduce for these types of ...the data for the MapReduce tasks to be in its distributed file system but currently there is no ...
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MapReduce and Data Intensive Applications
... static/loop-invariant data in memory between iterations; HaLoop extends Hadoop and supports loop-invariant caching and also keeps the reduced outputs in memory in order to provide a faster fix point scheduling; ...
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Map Reduce for Data Intensive Scientific Analyses
... store data as well as the intermediate ...the data to be dispersed at all the data/computing ...replicates data on multiple nodes so that a failure of nodes containing a portion of the ...
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Biomedical Case Studies in Data Intensive Computing
... full data set we used for this research consists of over 314,000 real-life patient records collected over 15 years and measured on about 180 variables, mostly related with biological and environmental ...full ...
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Classifying Simulation and Data Intensive Applications and the HPC-Big Data Convergence
... Mainly Data vi. Variety: important property especially of composite Ogres; Data and Model separately ...kernels; Data and Model separately ...
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Designing Data Intensive Web Applications fly pdf
... of data-centric user in- terface in general with units and links, WebML doesn’t rest on its ...through data, these formalisms both enable a huge range of possibilities and save a huge amount of developer ...
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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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Data classification algorithm for data intensive computing environments
... training data set increases. When there is only a small amount of data, HDFS needs to split the training data and store the distribution in the data nodes; therefore, the pre- processing time ...
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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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Sensors and other 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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Towards Efficient and Scalable Data Intensive Content Delivery: State of the Art, Issues and Challenges
... Content Distribution: The delivery infrastructure of video operators is made up of scattered geo-distributed servers, which with specific cache selection mech- anisms direct users to the closest servers hosting the ...
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Training in data definitions improves quality of intensive care data
... to data definitions decreased the most after training. Incomplete data mostly concerned respiratory rate and mean blood ...Inaccurate data from outside the first 24 hours of intensive care ...
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Pharmacokinetic variability and exposures of fluconazole, anidulafungin, and caspofungin in intensive care unit patients: Data from multinational Defining Antibiotic Levels in Intensive care unit (DALI) patients Study
... Anidulafungin blood samples were collected from 10 ICU patients, with one patient excluded as PK parameters could not be estimated from available data. As such, the study sample consisted of nine patients from ...
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Data Intensive Computing for Bioinformatics
... demanding data analysis ...“doubly data parallel” computations in two important bioinformatics sequencing applications, and use the results to compare two implementations of MapReduce (Dryad and Hadoop) ...
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Performance Evaluation of MapReduce applications on Cloud Computing Environment, FutureGrid
... of data in a parallel fashion. It is a kind of data parallel languages aimed at loosely coupled computations that execute over given data sets ...
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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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