[PDF] Top 20 Twister: A Runtime for Iterative MapReduce
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Twister: A Runtime for Iterative MapReduce
... 5. Geoffrey Fox, Seung-Hee Bae, Jaliya Ekanayake, Xiaohong Qiu, and Huapeng Yuan, Parallel Data Mining from Multicore to Cloudy Grids, High Performance Computing and Grids workshop, 2008. – An extended version of this ... See full document
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Twister: A Runtime for Iterative MapReduce
... implementing Twister - a distributed in-memory MapReduce runtime optimized for iterative MapReduce ...of Twister and its architecture comparing them with the typical ... See full document
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The Cost Effective Iterative MapReduce in Big Data Environment K Chandra Sekhar & P Karthik
... for iterative applications, it also dramatically improves their efficiency by making the task scheduler loop-aware and by adding various caching mechanisms Ekanayake et al [9] proposed framework known as ... See full document
6
Performance Analysis of Twister based MapReduce Applications on Virtualization System in FutureGrid
... 2.2 Twister There are some existing implementations of MapReduce such as Hadoop [6] and Sphere ...[7]. Twister is one of MapReduce implementations that is an enhanced MapReduce ... See full document
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Collective Communication Patterns for Iterative MapReduce
... announced iterative MapReduce runtime developed by Microsoft Research for Microsoft Azure Cloud Platform that builds on some of the ideas of the earlier Twister ... See full document
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Dynamically Iterative MapReduce
... Hadoop MapReduce The MapReduce architecture in Hadoop [9] is shown in ...1. MapReduce is composed by the one Master as well as a number of Map blocks and Reduce ...blocks. MapReduce works ... See full document
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Classical and Iterative MapReduce on Azure
... Azure Queues for scheduling, Tables to store meta-data and monitoring data, Blobs for input/output/intermediate data storage... MapReduceRoles4Azure.[r] ... See full document
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MrLazy: Lazy Runtime Label Propagation for MapReduce
... System MapReduce is a paradigm [7] for large-scale data process- ing and ...Moreover MapReduce is tolerant to failures as erro- neous and incomplete tasks can be restarted independently of each ...of ... See full document
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Generalizing MapReduce as a Unified Cloud and HPC Runtime
... MDS Output Monitoring Interface Pub/Sub Broker Network Worker Node Worker Pool Twister Daemon Master Node Twister Driver Twister-MDS Worker Node Worker Pool Twister Daemon map reduce map[r] ... See full document
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Iterative MapReduce and High Performance Datamining
... Classic MapReduce as in Hadoop; single Map followed by reduction with fault tolerant use of disk 3) Iterative MapReduce use for data mining such as Expectation Maximization in clustering ... See full document
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Towards Predicting the Runtime of Iterative Analytics with PREDIcT
... other iterative algorithms executing graph process- ing tasks such as: random walks with restart [22] (prox- imity estimation), or Markov clustering [37] are expected to benefit from similar sampling methods based ... See full document
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A Game-Theoretic Approach for Runtime Capacity Allocation in MapReduce
... for runtime capacity allocation, based on Game Theory models and techniques, that mimics the Map- Reduce dynamics by means of interacting players, namely the central Resource Manager and Class ... See full document
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MapReduce particle filtering with exact resampling and deterministic runtime
... the MapReduce framework: as a result, while we can achieve a speed-up of 3-fold with 16 cores in a single node, with 512 cores spread across 28 nodes, we only achieve a speed-up of approximately ... See full document
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MapReduce particle filtering with exact resampling and deterministic runtime
... Prior to mapping the particle filter algorithm on to a MapReduce form, it is essential to understand how the operations used by a particle filter can be implemented in a fully distributed form. While a more ... See full document
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Mining Uncertain Sequential Patterns in Iterative MapReduce
... In this paper, we propose a SPM algorithm in an iterative MapReduce framework for large scale uncertain databases to discover customer behavior patterns in Amazon review dataset.. In the[r] ... See full document
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Twister4Azure: Iterative MapReduce for Windows Azure Cloud
... Azure Queues for scheduling, Tables to store meta-data and monitoring data, Blobs for input/output/intermediate data storage... Data Intensive Iterative Applications[r] ... See full document
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Iterative MapReduce Enabling HPC Cloud Interoperability
... 5 • Users submit their jobs to the pipeline and the results will be shown in a visualization tool. • This chart illustrate a hybrid model with MapReduce and MPI. Twister will be an unified solution for the ... See full document
81
MapReduce, GPGPU and Iterative Data mining algorithms
... using iterative majorization to –d ix , the problem is solved by equation: • By applying MDS-interpolation, the author has visualized up to 2 million data points by using 32 nodes / 768 ... See full document
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Accelerating Data Transfers In Iterative MapReduce Framework
... several iterative MapReduce frameworks including our Twister system have emerged to improve the performance on many important data mining ...accelerate MapReduce execution but we still find ... See full document
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Processing Weather Sensor Data Using Iterative MapReduce Approach
... Data analysis is an important functionality in cloud computing which allows a huge amount of data to be processed over very large clusters. Map Reduce is recognized as a popular way to handle data in the cloud ... See full document
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