Data Intensive Scalable Computing
Architecture and Performance of Runtime Environments for Data Intensive Scalable Computing
... Jaliya Ekanayake, Advisor: Geoffrey Fox Architecture and Performance of Runtime Environments for Data Intensive Scalable Computing, Accepted for the Doctoral Showcase, SuperComputing2009[r] ...
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Architecture and Performance of Runtime Environments for Data Intensive Scalable Computing
... 4 Pleasingly Parallel Each component is independent. In 1988, Fox estimated this at 20% of the total number of applications but that percentage has grown with the use of Grids and data analysis applications as ...
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ARCHITECTURE AND PERFORMANCE OF RUNTIME ENVIRONMENTS FOR DATA INTENSIVE SCALABLE COMPUTING
... The possibility in supporting fault tolerance easily is one of the key benefits of the MapReduce programming model. However, with the use of stateful tasks, this possibility will no longer be in effect, because the tasks ...
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Doctorat ParisTech T H È S E. TELECOM ParisTech. Size-Based Disciplines for Job Scheduling in Data-Intensive Scalable Computing Systems
... Scheduling is one of the most studied problems in many fields, and in particular in com- puter science. From an abstract perspective, the scheduling problem can be seen as follows: given a set of resources and a set of ...
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Scalable Programming and Algorithms for Data Intensive Life Science Applications
... SALSA project (salsahpc.indiana.edu) investigates new programming models of parallel multicore computing and Cloud/Grid computing. It aims at developing and applying parallel and distributed ...
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Review On Data Replication with QoS and Energy Consumption for Data Intensive Applications in Cloud Computing
... Cloud computing, a large pool of systems is connected in private or public networks which provide dynamically scalable infrastructure for applications, data and file ...Cloud Computing ...
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An extensible and scalable Pilot-MapReduce framework for data intensive applications on distributed cyberinfrastructure
... distributed infrastructures effectively made the design and development of distributed applications more complex task [23]. For example, many programming systems and tools for distributed appli- cations are either ...
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INFO H516 Applied Cloud Computing for Data Intensive Sciences
... covers data science concepts, techniques, and tools to support big data analytics, including cloud computing, parallel algorithms, nonrelational databases, and high-level language ...utility ...
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Towards Efficient and Scalable Data Intensive Content Delivery: State of the Art, Issues and Challenges
... Ubiquitous Computing can be categorized to (Want and Per- ing [170]): (i) power management issues: refers to how mobile devices deal with processing power and storage space and the kind of wireless technology to ...
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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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Research on High-performance and Scalable Data Access in Parallel Big Data Computing
... a scalable locality-aware middleware (SLAM), which allows scientific analysis applications to benefit from data-locality exploitation with the use of HDFS, while also maintaining the flexibility and ...
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Scalable Data Analysis in High Performance Computing
... of data-oriented and data-intensive services ...science data collection [6], or the planned radio observatory Square Kilometer Array (SKA) [7]—collect an ex- ponentially growing amount of ...
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Hybrid Cloud and Cluster Computing Paradigms for Scalable Data Intensive Applications
... Need is pervasive – Large and high dimensional data are everywhere: biology, physics, Internet, … – Visualization can help data analysis Visualization of large datasets with high perform[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
... 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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Big Data Clustering Using Heuristic Data Intensive Computing and Self Organizing Maps
... Heuristic Data Intensive Computing (HDIC) Heuristic means set of rules that are used to increase the probability of solving a ...of data into another form of data. Data ...
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Improvement of Data-Intensive Applications Running on Cloud Computing Clusters
... to data popularity in order to get better performance and disk ...real-time data types, ERMS utilizes a complex event processing ...hot data, while it cleans up these extra replicas when the ...
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Time and Cost Sensitive Data-Intensive Computing on Hybrid Clouds
... transactional data store [6], data-intensive web services [11], a cache that accelerates data-intensive applications [5], and for execution of a bag of tasks ...
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Low-Power Amdahl-Balanced Blades for Data-Intensive Computing
... Alex Szalay , Andreas Terzis, Alainna White, Howie Huang, Jan Vandenberg, Ani Thakar, Tamas Budavari, Sam Carliles, Alireza Murazavi, Gordon Bell, Jose Blakeley, David Luebke, Michae[r] ...
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Scalable Parallel Computing on Clouds
... Contributions • Highly available, scalable decentralized iterative MapReduce architecture on eventual consistent services • More natural Iterative programming model extensions to MapRedu[r] ...
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Parrot: Transparent User-Level Middleware for Data-Intensive Computing
... trap an modify any system all, the remote lesystem and kernel allout tehniques are limited to lesystem.. operations.[r] ...
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