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Masters Project Report and Presentation

Download (PPTX, 1.43MB)

Download (DOCX, 1.17MB)

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Compute Grid Presentation

Download (PPTX, 934KB)

Posted in Advanced Parallel Computing, General, Masters Project Leave a comment

Switching to Weka?

My application is currently utilizing the Java-ML library to run Machine Learning algorithms. It appears that support for Java-ML is pretty limited, and Weka (http://www.cs.waikato.ac.nz/ml/weka/) appears to be a more commonly used platform. I am currently evaluating utilizing the Weka library instead of Java-ML.

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Masters Paper Outline

  • Introduction to Distributed Machine Learning
    • When to run distributed?
    • Premise of research (Point being made)
  • A look at other Distributed Machine Learning frameworks
    • H20
    • MLBase (Spark & MLLib)
  • Explanation of research and project
    • Why Apache Ignite?
      • Integration with Hadoop
      • Caching features
    • Ignite Vs. Spark
  • Future work
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Masters Project Goals

  • Research current technologies available in the domain of Distributed Machine Learning
  • Perform comparisons of other available technologies
  • Develop application to integrate with the Apache Ignite Data Fabric that perform distributed machine learning
    • Often Apache Ignite is compared with Apache Spark
      • Spark has a machine learning library called MLLib
      • Apache Ignite has no machine learning integration currently
    • It’s my belief that Apache Ignite is a great practical platform that can be extended to abstract machine learning algorithms for practical use
  • Write a paper to show an overview of the current technologies, as well as my project
    • Explain the advantages over the other platforms
  • Prepare for additional research at Clarkson University
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Apache Ignite Vs. MPI (Message Passing Interface)

Apache Ignite

  • Compute Grid
    • Any node can be an orchestrator
  • Automatic network association
    • Nodes deployed on the network running Apache Ignite will automatically associate
  • Highly Portable
    • The only dependency the nodes require is Java
    • Machines do no need to be identical
    • All resources pool together
  • Runs in a virtual environment
    • Many times, Java is viewed negatively because it runs in a virtual environment, however it has since been optimized to be more reliable and fast

MPI (Message Passing Interface)

  • Beowulf Cluster
    • Requires a master node for orchestration
  • Requires network configuration
    • Nodes must be configured to communicate without authentication
  • Claims Portability
    • MPI is portable, however there can be issues with C libraries that are platform dependent
  • Does not have overhead from running virtualized (like Java)
Posted in Advanced Parallel Computing Leave a comment

Ignite Compute Grid

in_memory_compute

As shown in the past, Apache Ignite is a very rich software platform. In the past, the Apache Ignite Data Grid has been presented. Relating to Advanced Parallel Computing, the Apache Ignite Compute Grid will be researched.

The Apache Ignite Compute grid is built for high performance, low latency, and scalability. I think one of the most impressive aspects of Apache Ignite is the thought put into interfaces, and integration. Ignite really allows integrators to easily develop in utilizing their framework.

The Ignite Compute Grid provides a great availability scheme. Basically, as long as there is at least one node available, your closure is guaranteed to execute. Of course I have haven’t explained what a closure is yet, but it’s similar to a Lambda to give an idea. Basically a small chunk of executable code.

The Ignite Compute Grid provides a fail-over mechanism as part of it’s load balancing functionality. The computing power of a node on the grid will be considered when executing tasks. The load balancer manages tasks to ensure they are running optimally.

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Starting Java Development

Context

This post will apply both to my CS528 Advanced Parallel Computing and CS598 Masters Project courses since both utilize Apache Ignite. These are the tools that I needed to apply to get started with Apache Ignite.

  • Java 8 JDK (Java Development Kit)
  • Netbeans 8.1
  • Apache Maven 3.0.5

Java 8

Installing Java 8 should be fairly simple. The installation file can be downloaded from: http://www.oracle.com/technetwork/java/javase/downloads/index.html

The installation should be simple as well. Follow the steps in the installer. The default location will be in Program Files (may depend on 32 vs 64 bit version).

Netbeans 8.1

While I suggest using Netbeans as a development IDE (Integrated Development Environment), one could just as easily use Eclipse. The installation of Netbeans should also be straightforward. Follow the steps laid out in the installer. There may be some configuration to follow to ensure your Netbeans instance points to your newly installed JDK. If I am not mistaken, I think it may automatically look for your JDK during install.

Apache Maven 3.0.5

Apache Maven is a build system with dependency management built in. With the utilization of .pom files, one can structure builds and automatically resolve dependencies from remote hosted repositories. Many of the repos are hosted by trusted sources. When a dependency is needed, Maven will first look to see if it exists in your local repository. If it does not exist or is older than a remote version, then it will be retrieved from the remote repository.

Configuring Netbeans to utilize Maven

After installing Maven, it is important to make sure that your Netbeans install is pointing at your recently installed Maven. This can be achieved by: Launching Netbeans, click “Tools”, then click “Options”, and finally navigate to “Java-> Maven”. You should have the
“Maven Home” configuration item set to your newly installed Apache Maven.

 

This guide has been created to prepare an individual for developing Apache Ignite hosted applications, however it could also be utilizing for anyone looking to start developing in Java. I hope what’s provided here is helpful, and I hope you enjoy my content!

Posted in Advanced Parallel Computing, Apache Ignite, Masters Project Tagged apache, ignite, java Leave a comment

Apache Ignite Compute Grid

Compute Grid

apache-ignite

In the past, I had reported on the Data Grid component of Apache Ignite, but the focus of my research in CS 528 (Advanced Parallel Computing) and CS 598 (Masters Project) will be the Apache Ignite Compute Grid.

in_memory_compute

The compute grid is a cluster of resources that can be used to perform distributed computations. The diagram above depicts the flow of the compute grid. Computations are sent to the distributed cluster, and then results are aggregated when available. More to come soon!

 

Posted in Advanced Parallel Computing, Advanced Parallel Computing Seminar, Masters Project Leave a comment
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