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  1. Proceedings of the Fourth Conference on Partitioned Global Address Space Programming Model (PGAS '10)
  2. X10-enabled MapReduce
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Predicting remote reuse distance patterns in UPC applications
Introducing OpenSHMEM: SHMEM for the PGAS community
Hybrid PGAS runtime support for multicore nodes
Asynchronous PGAS runtime for Myrinet networks
Unifying UPC and MPI runtimes: experience with MVAPICH
Introducing mNUMA: an extended PGAS architecture
Performance modeling for multilevel communication in SHMEM+
Improving UPC productivity via integrated development tools
X10-enabled MapReduce
Development and performance analysis of a UPC Particle-in-Cell code
XcalableMP implementation and performance of NAS Parallel Benchmarks
Extensible PGAS semantics for C++
An open-source compiler and runtime implementation for Coarray Fortran
Hiding latency in Coarray Fortran 2.0
Numerical Python for scalable architectures

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X10-enabled MapReduce

Content Provider ACM Digital Library
Author Grove, David Zhou, Shujia Dong, Han
Abstract The MapReduce framework has become a popular and powerful tool to process large datasets in parallel over a cluster of computing nodes [1]. Currently, there are many flavors of implementations of MapReduce, among which the most popular is the Hadoop implementation in Java [5]. However, these implementations either rely on third-party file systems for across-computer-node communication or are difficult to implement with socket programming or communication libraries such as MPI. To address these challenges, we investigated utilizing the X10 language to implement MapReduce and tested it with the word-count use case. The key performance factor in implementing MapReduce is data moving across different computer nodes. Since X10 has built-in functions for across-node communication such as distributed arrays [2], a major challenge with MapReduce implementations is easily solved. We tested two main implementations: the first utilizes the HashMap data structure and the second a Rail with elements consisting of a string and integer pair. The performance of these two implementations are analyzed and discussed.
Starting Page 1
Ending Page 6
Page Count 6
File Format PDF
ISBN 9781450304610
DOI 10.1145/2020373.2020382
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2010-10-12
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Mapreduce Pgas Across-node-communication
Content Type Text
Resource Type Article
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