Parallel Programming

Hadoop is an open source distributed parallel programming framework that realizes the MapReduce computing model, with the help of Hadoop, programmers can easily write distributed parallel program, run it on computer cluster, and complete the computation of massive data. This paper will introduce the basic concepts of MapReduce computing model, distributed parallel computing, and the installation and deployment of Hadoop and its basic operation methods. Introduction to Hadoop Hadoop is an open-source, distributed, parallel programming framework that can run on large clusters.

Hadoop is an open source distributed parallel programming framework that realizes the MapReduce computing model, with the help of Hadoop, programmers can easily write distributed parallel program, run it on computer cluster, and complete the computation of massive data. This paper will introduce the basic concepts of MapReduce computing model, distributed parallel computing, and the installation and deployment of Hadoop and its basic operation methods. Introduction to Hadoop Hadoop is an open-source, distributed, parallel programming framework that can be run on a large scale cluster by ...

MapReduce is a distributed programming model developed by Google for mass data processing in large-scale groups. It implements two functions: map applies a function to all members of the collection, and then returns a result set based on this processing. and reduce is the classification and generalization of result sets that are processed in parallel by multiple threads, processes, or stand-alone systems from two or more maps. The Map () and Reduce () two functions may run in parallel, even if not in the same system ...

program example and Analysis Hadoop is an open source distributed parallel programming framework that realizes the MapReduce computing model, with the help of Hadoop, programmers can easily write a distributed parallel program, run it on a computer cluster, and complete the computation of massive data. In this article, we detail how to write a program based on Hadoop for a specific parallel computing task, and how to compile and run the Hadoop program in the ECLIPSE environment using IBM MapReduce Tools. Preface ...

Foreword in the first article of this series: using Hadoop for distributed parallel programming, part 1th: Basic concepts and installation deployment, introduced the MapReduce computing model, Distributed File System HDFS, distributed parallel Computing and other basic principles, and detailed how to install Hadoop, How to run a parallel program based on Hadoop in a stand-alone and pseudo distributed environment (with multiple process simulations on a single machine). In the second article of this series: using Hadoop for distributed parallel programming, ...

Foreword in an article: "Using Hadoop for distributed parallel programming the first part of the basic concept and installation Deployment", introduced the MapReduce computing model, Distributed File System HDFS, distributed parallel Computing and other basic principles, and detailed how to install Hadoop, how to run based on A parallel program for Hadoop. In this article, we will describe how to write parallel programs based on Hadoop and how to use the Hadoop ecli developed by IBM for a specific computing task.

Beijing time this morning, Intel (Intel) officially released the Xeon Phi (Xeon) coprocessor based on an integrated Salt Lake City (MIC) architecture at the supercomputer (SC12) Conference held in the city. One of the Xeon Phi coprocessor 5110P with the date of shipment, January 28, 2013 GA, recommended customer price of 2649 dollars; Xeon Phi Coprocessor 3,110 families will be available in the first half of 2013, advising customers price less than 2000 U.S. dollars. Intel Xeon Phi Coprocessor Home ...

Cable-Bell filter technology based on parallel programming computation Xu Changlong Wang Smart Shuo Hua with the increase of the data volume of remote sensing image, the computation time of the edge filtering operation in a single environment is also greatly increased. According to the characteristics of remote sensing data, combined with MapReduce parallel distributed computing model, this paper proposes a method of migrating this operation into Hadoop cluster environment to complete the Bayes filtering operation of massive image data. The experimental results show that the cluster operation can shorten the computation time, and the calculation time will decrease with the increase of cluster node number. ...

Cable-Bell filter technology based on parallel programming computing model Xu Changlong Wang clever Shuo Hua with the increase of the data of remote sensing image, the computation time of the edge filtering operation of the cable-bell in single environment is also increased. According to the characteristics of remote sensing data, combined with MapReduce parallel distributed computing model, this paper proposes a method of migrating this operation into Hadoop cluster environment to complete the Bayes filtering operation of massive image data. The experimental results show that the cluster operation can shorten the computation time, and the calculation time will decrease with the increase of cluster node number. ...

One months ago, I was asked what is functional programming? Although familiar with some of the concept of functional programming, the Little Schemer bought from Canada six months ago also read the previous chapters, that day is not able to answer what is functional programming. Functional programming is a strange field for programmers familiar with procedural programming, and concepts such as closures (closure), continuations (continuation), and currying are a nightmare for programmers with procedural programming. Without u ...