دانلود رایگان مقاله لاتین برنامه نویسی نگاشت کاهش برای برنامه کاربردی ابری مواد از سایت الزویر
عنوان فارسی مقاله:
MaMR: مدل برنامه نویسی نگاشت کاهش با عملکرد بالا برای برنامه های کاربردی ابری مواد
عنوان انگلیسی مقاله:
MaMR: High-performance MapReduce programming model for material cloud applications
سال انتشار : 2016
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مقدمه انگلیسی مقاله:
1. Introduction
In recent years, a large number of known and hypotheticalmaterials have been studied, such as batteries, catalysts, and thestable structures of solid materials, so the amount of calculateddata increases exponentially with time [1]. Thus, big data presentsa huge challenge to the computing disciplines.To improve computing speed, a large number of computingtasks in materials science must be moved from traditional HighPerformanceComputing (HPC) to High-Throughput Computing(HTC) and Many-Task Computing (MTC) platforms based on bigdata, such as the widely used cloud computing systems [2] and gridcomputing [3].As is known, cloud computing, which should provide differentlayers of service to users, is constituted by large-scale distributedcomputers and various resources such as CPUs and storage. Meanwhile,different types of services are also offered, such as software[4]. In cloud computing systems, multiple virtual machines (VMs) are run on a single physical computer, for a homogeneousresult [5].It is more convenient to develop and deploy applicationsthrough the cloud computing platform, Therefore, in this paper,we adopt this approach to process large amounts of materialdata. We use cloud computing’s powerful computation and storagecapacity to effectively solve the problem of large-scale materialdata in the process of analytical calculations. To fit the materialhigh-performance computing needs of materials science, differentmodels have been proposed to maximize the performance.Meanwhile, to provide greater flexibility and higher parallelefficiency, the challenges to the programming model should befaced [6]. The MapReduce programming model has been widelyused in large-scale and data-intensive applications, such as Googleand Amazon [7,8]. The other most successful programming modelis Microsoft’s Dryad [9]. Yahoo also has similar infrastructures.Hadoop is an open-source implementation of MapReduce, and ithas already been applied to various fields because of the reliabilityand scalability of the parallel programming framework in theMapReduce model [10]. In Hadoop and MapReduce, the input dataare split into chunks of size 64 M, and each task is allocated to a VM.Therefore, we can take the computation nodes as the local modes.However, traditional programming models cannot adapt tomaterial data calculations, and Hadoop’s frequent reading and writing become the bottleneck of the cloud system. First, in a cloudcomputing system, many computing jobs are running in a singlephysical computer because the data nodes in Hadoop are deployedin virtual machines. How to avoid I/O resource competition andreduce I/O overhead is a big problem in the programming modelsfor cloud computing.
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کلمات کلیدی:
MaMR: High-performance MapReduce programming model for ... - خانهzoodyab.ir/.../157299-mamr-high-performance-mapreduce-progra...Translate this pageTo enhance the capability of workflow applications in material data processing, we defined a programming model for material cloud applications that supports ...[PDF]Large-Scale Image Classification using High Performance Clusteringdsc.soic.indiana.edu/.../Large-Scale_Image_Classification_using_High_Performance_...by B Zhang - Cited by 1 - Related articlesLarge-Scale Image Classification using High Performance Clustering ... MapReduce computation, leading to the iterative MapReduce programming .... histogram over this vocabulary: given an image, we densely sample patches, compute HOG ...... “PortLand: A Scalable Fault-Tolerant Layer 2 Data Center Network Fabric.”.[PDF]MapReduce for Scientist using FutureGrid - Digital Science Centerdsc.soic.indiana.edu/publications/CCGrid%20tutorial.pdfMapReduce programming model has simplified the implementations of many ... demonstrate Map reduce environments in FG utilizing traditional high-performance ... The tutorial will be available online as part of the FG educational material.Exploring performance models of Hadoop applications on cloud ...ieeexplore.ieee.org/document/7450806/by X Wu - 2015 - Cited by 3 - Related articlesAbstract: Hadoop is an open source implementation of the MapReduce programming model, and provides the runtime infrastructure for map and reduce ...A Coarse-Grained Reconfigurable Architecture for Compute-Intensive ...ieeexplore.ieee.org/document/7163277/by S Liang - 2016 - Related articlesAlthough processors such as GPGPUs and FPGAs show good performance of speedup, there is still vacancy for a low power, high efficiency and ... a dynamically reconfigurable acceleration to MapReduce-based (MR-based) applications. ... board, and a programming model with compilation flow for CGRA is presented.MapReduce - Wikipediahttps://en.wikipedia.org/wiki/MapReduceMapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel, distributed algorithm on a ...Big Data Tutorial 1: MapReduce - High Performance Computing at ...https://wikis.nyu.edu/display/NYUHPC/Big+Data+Tutorial+1%3A+MapReduceApr 12, 2017 - HDFS provides high throughput access to application data and is suitable for ... MapReduce is a programming model and an associated ...
