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Digital Signal Processing, Data Analytics, Big Data, HPC
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Parallel Tempering in R with Rmpi - Lindons Log

Parallel Tempering in R with Rmpi - Lindons Log | EEDSP | Scoop.it
An introduction to parallel and distributed computing in R using Rmpi exemplified by parallel tempering - metropolis coupled Markov chain monte carlo mcmc.
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Using the Intel® MPI Library on Intel® Xeon Phi™ Coprocessor Systems | Intel® Developer Zone

Using the Intel® MPI Library on Intel® Xeon Phi™ Coprocessor Systems | Intel® Developer Zone | EEDSP | Scoop.it

This document is designed to help users get started writing code and running Message Passing Interface (MPI) applications (using the Intel® MPI library) on a development platform that includes the Intel® Xeon Phi™ Coprocessor.

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Using the Intel® MPI Library in a server/client setup

Using the Intel® MPI Library in a server/client setup | EEDSP | Scoop.it
A guide for using the MPI_Comm_accept and MPI_Comm_connect functions to form a server/client program suite with the Intel® MPI Library.
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Hama - a Bulk Synchronous Parallel computing framework on top of Hadoop

Apache Hama is a pure BSP (Bulk Synchronous Parallel) computing framework on top of HDFS (Hadoop Distributed File System) for massive scientific computations such as matrix, graph and network algorithms.

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GraphLab - Large-Scale Machine Learning on Graphs

GraphLab is an open source project to produce free implementations of scalable machine learning algorithms on multicore machine and clusters. The project was initiated in 2009 by Prof. Carlos Guestrin from Carnegie Mellon University and Prof. Joseph Hellerstein from University of California, Berkeley. GraphLab is a rapidly growing project with a large user base. As for October 2011, approximately 2000 institutions around the world installed Graphlab, including academia, research labs and industry

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