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  • Book Overview & Buying Building a BeagleBone Black Super Cluster
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Building a BeagleBone Black Super Cluster

Building a BeagleBone Black Super Cluster

By : Andreas J Reichel
4.5 (4)
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Building a BeagleBone Black Super Cluster

Building a BeagleBone Black Super Cluster

4.5 (4)
By: Andreas J Reichel
Buy this Book

Overview of this book

If you are a programmer, scientist, or someone interested in modern computer technology that goes beyond the typical PC, then this book will show you the outstanding possibilities of cluster computing with modern embedded systems based on ARM architecture. Whether you need a high-speed or low-cost scalable cluster for simulations or want to try something new, this book is the right guide for you.
Table of Contents (9 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. BeagleBone Black System Board
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1. BeagleBone Black System Board
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Introducing the hardware
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The storage memory partition structure
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The boot-selection button
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Operating systems
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Software programming
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Summary
2
2. Building a Beowulf Cluster
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2. Building a Beowulf Cluster
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Minimal configuration and optional equipment
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Building a scalable board-mounting system
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Using a low-cost power source
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Setting up the network backbone
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The network topology
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The storage memory
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Summary
3
3. Operating System Setup and Configuration
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3. Operating System Setup and Configuration
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The Linux host environment
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Creating the master node's installation image
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Installing the operating system on the master node
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The external network storage
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Installing and configuring the slave nodes
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A crash course in developing applications
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Transferring files from and to the BeagleBone master node
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Summary
4
4. Parallel Computing with OpenMPI and ScaLAPACK
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4. Parallel Computing with OpenMPI and ScaLAPACK
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MPI – Message Passing Interface
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Installing and configuring OpenMPI
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Installing and configuring ScaLAPACK
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Summary
5
5. Advanced Solving of General Equation Systems
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5. Advanced Solving of General Equation Systems
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PETSc – a toolkit for scientific computation
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SLEPc – a library for Eigenvalue problems
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Summary
6
6. Scientific and Technological Examples of Parallel Computing
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6. Scientific and Technological Examples of Parallel Computing
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Calculations on cloud-distributed mesh grids
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deal.II – a powerful Physics calculation library
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Example programs
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Parallel solution of elastic equations
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The visualization of calculated data
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Summary
7
A. References
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A. References
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Index
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Index

Chapter 4. Parallel Computing with OpenMPI and ScaLAPACK

The advantage of a cluster compared to a normal personal computer is its capability of performing tasks in parallel and thereby reducing the overall calculation time. On modern computer platforms, there are two main architectures that perform parallel computations:

  • Shared memory systems
  • Distributed memory systems

On the shared memory system architecture, different CPUs or CPU cores share the same main memory. This means that every program that is loaded from one core or CPU can principally be used by other cores or CPUs as well. To optimally use such a system, the memory or process management has to take care that two processes do not access the same locations of the shared main memory at the same time. Otherwise, one process might have to wait for another until it has completed its operation or freed some locked resources. Also, software programmers have to take care of the fact that only one process can alter such memory...

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Building a BeagleBone Black Super Cluster
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