• MapReduce

  • Referenced in 250 articles [sw00546]
  • MapReduce is a new parallel programming model initially developed for large-scale web content processing ... over extremely large datasets. The arrival of MapReduce provides a chance to utilize commodity hardware ... optimization from relational algebra operators to MapReduce programs is still an open and dynamic research ... first study the communication cost of the MapReduce model, then we give an initial implementation...
  • Spark

  • Referenced in 34 articles [sw23653]
  • Spark: cluster computing with working sets. MapReduce and its variants have been highly successful ... retaining the scalability and fault tolerance of MapReduce. To achieve these goals, Spark introduces...
  • GraphLab

  • Referenced in 22 articles [sw12830]
  • challenging. Existing high-level parallel abstractions like MapReduce are insufficiently expressive while low-level tools ... developed GraphLab, which improves upon abstractions like MapReduce by compactly expressing asynchronous iterative algorithms with...
  • G-Hadoop

  • Referenced in 12 articles [sw08480]
  • data computing across distributed cloud data centres. MapReduce is regarded as an adequate programming model ... Hadoop framework is a well-known MapReduce implementation that runs the MapReduce tasks ... Hadoop is an extension of the Hadoop MapReduce framework with the functionality of allowing ... MapReduce tasks to run on multiple clusters. However, G-Hadoop simply reuses the user authentication...
  • GATK

  • Referenced in 14 articles [sw12019]
  • genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Next-generation ... sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich...
  • Twister

  • Referenced in 7 articles [sw27735]
  • Twister: a runtime for iterative MapReduce. MapReduce programming model has simplified the implementation of many ... services provided by many implementations of MapReduce attract a lot of enthusiasm among distributed computing ... From the years of experience in applying MapReduce to various scientific applications we identified ... architecture that will expand the applicability of MapReduce to more classes of applications. In this...
  • CloudBurst

  • Referenced in 7 articles [sw12025]
  • CloudBurst: highly sensitive read mapping with MapReduce. Motivation: Next-generation DNA sequencing machines are generating ... uses the open-source Hadoop implementation of MapReduce to parallelize execution using multiple compute nodes ... model for parallelizing algorithms with MapReduce at http://cloudburst-bio.sourceforge.net...
  • WebPIE

  • Referenced in 6 articles [sw12482]
  • scale parallel inference engine using MapReduce. The large amount of Semantic Web data ... Horst semantics using the MapReduce programming model. We will show that a straightforward implementation...
  • PLANET

  • Referenced in 5 articles [sw15434]
  • Massively parallel learning of tree ensembles with mapreduce. Classification and regression tree learning on massive ... computations, and implements each one using the MapReduce model of distributed computation. We show ... benefits and challenges of using a MapReduce compute cluster for tree learning, and demonstrate...
  • MrsRF

  • Referenced in 4 articles [sw12018]
  • MrsRF: an efficient MapReduce algorithm for analyzing large collections of evolutionary trees. MapReduce ... paper, we evaluate the viability of the MapReduce framework for designing phylogenetic applications. The problem ... collections of evolutionary trees. We introduce MrsRF (MapReduce Speeds up RF), a multi-core algorithm ... distance matrix between t trees using the MapReduce paradigm...
  • PEGASUS

  • Referenced in 8 articles [sw17479]
  • Hadoop platform, the open source version of MapReduce. Many graph mining operations (PageRank, spectral clustering...
  • BlobSeer

  • Referenced in 5 articles [sw10569]
  • storage backend in the Hadoop MapReduce framework. We perform extensive microbenchmarks as well as experiments ... with real MapReduce applications: they demonstrate that applying the principles defended in our approach brings...
  • DryadLINQ

  • Referenced in 7 articles [sw23712]
  • generalizes previous execution environments such as SQL, MapReduce, and Dryad in two ways: by adopting...
  • Geppetto

  • Referenced in 7 articles [sw31791]
  • sharing state between computations (e.g, For MapReduce) or within a single computation...
  • Dremel

  • Referenced in 6 articles [sw13849]
  • Dremel, and explain how it complements MapReduce-based computing. We present a novel columnar storage...
  • HaLoop

  • Referenced in 3 articles [sw27955]
  • modified version of the Hadoop MapReduce framework, designed to serve these applications. HaLoop not only ... extends MapReduce with programming support for iterative applications, but also dramatically improves their efficiency...
  • Vispark

  • Referenced in 2 articles [sw17471]
  • data processing in diverse application domains, MapReduce (e.g., Hadoop) has become one of the standard ... cluster system. Despite its popularity, the current MapReduce framework suffers from inflexibility and inefficiency inherent ... novel extension of Spark for GPU-accelerated MapReduce processing on array-based scientific computing ... syntax and a novel data abstraction for MapReduce programming on a GPU cluster system. Vispark...
  • iMapReduce

  • Referenced in 2 articles [sw27957]
  • data sets on a cluster of machines. MapReduce is an example of such a framework ... However, MapReduce lacks built-in support for iterative process that requires to parse data sets ... iteratively. Besides specifying MapReduce jobs, users have to write a driver program that submits ... reducing the overhead of creating new MapReduce jobs repeatedly, (2) eliminating the shuffling of static...
  • CloudBLAST

  • Referenced in 2 articles [sw12013]
  • CloudBLAST: combining MapReduce and virtualization on distributed resources for bioinformatics applications. This paper proposes ... distributed computing. The proposed approach uses the MapReduce paradigm to parallelize tools and manage their ... Hadoop, Virtual Workspaces, and ViNe as the MapReduce, virtual machine and virtual network technologies, respectively...
  • Grex

  • Referenced in 2 articles [sw17472]
  • Grex: An efficient MapReduce framework for graphics processing units. In this paper, we present ... MapReduce framework, called Grex, designed to leverage general purpose graphics processing units (GPUs) for parallel ... state-of-the-art GPU-based MapReduce frameworks for the tested applications...