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Table of Contents

Extensive Training Courses

We have linked to relevant training courses from other institutions.  
Rather than recreate them we recommend that you access them directly.
Here is a partial list from each site:
Cornell Virtual Workshops

Introduction to


  • Introduction to C Programming
  • Introduction to Fortran Programming
  • Introduction to Python
  • Introduction to R
  • MATLAB Programming
  • Introduction to GPU and CUDA
  • Parallel Computing Courses including MPI and OpenMP
  • Code Improvement
  • Data Management including Globus, HDF5 and VisIt
  • CyberInfrastructure Tutor from NCSA

    • Debugging Code
    • MPI
    • Introduction to Performance Tools
    • Introduction to Visualization
    • Parallel Computing

    Software Carpentry

    • The Unix Shell
    • Version Control with Git
    • Using Databases and SQL
    • Programming with Python
    • Programming with R
    • Programming with MATLAB
    • Automation and Make

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    Linux Self Guided 

    We run RHEL/CentOS 6 Linux on our high-performance systems.

    If you have never used Linux before or have had very limited use, read this useful guide:

    If you have learned Linux in the past but want a quick reference to the syntax of commands, then read this:

    Bash Cheat Sheet

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    Intel® Modern Code Training

    Intel brought a workshop to campus in 2014 and the material is covered here.  If you want to do any work on the Intel® Xeon Phi™ Coprocessors we have 40 of them installed in ElGato.  You can obtain "standard" queue access and can request access to the nodes with them installed. 

    Created by Colfax International and Intel, and based on the book, Parallel Programming and Optimization with Intel® Xeon Phi™ Coprocessors, this short video series provides an overview of practical parallel programming and optimization with a focus on using the Intel® Many Integrated Core Architecture (Intel® MIC Architecture).

    Length: 5 hours

    Parallel Programming and Optimization with Intel Xeon Phi Coprocessors

    Intel® Software Tools

    Intel offers the Cluster Studio XE.  On Ocelote we have installed modules (module avail intel ) as:

    • intel-cluster-checker/2.2.2

    • intel-cluster-runtime/ia32/3.8

    • intel-cluster-runtime/intel64/3.8

    • intel-cluster-runtime/mic/3.8

    We have installed the Intel high performance libraries (module avail intel ):

    • Intel® Threading Building Blocks
    • Intel® Integrated Performance Primitives
    • Intel® Math Kernel Library
    • Intel® Data Analytics Acceleration Library

    The University is licensed and has access to this toolset separate from HPC.   Portions of it are FREE for use in teaching/instruction and to students.


    Introduction to Parallel Computing

    Thanks to Lawrence Livermore Labs for this tutorial

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    Introduction to OpenMP

    This PDF file is a presentation from a series called Xsede *  HPC HPC Workshop.

    View file

    * XSEDE, the Extreme Science and Engineering Discovery Environment, is the most advanced, powerful, and robust collection of integrated digital resources and services in the world. It is a single virtual system that scientists and researchers can use to interactively share computing resources, data, and expertise. XSEDE integrates the resources and services, makes them easier to use, and helps more people use them.





    Singularity containers let users run applications in a Linux environment of their choosing.  This is different from Docker which is not appropriate for HPC due to security concerns.  Singularity is like a container for Docker images, but is not just for Docker.  

    The most important thing to know is that you create the singularity container called an image on a workstation where you have root privileges, and then transfer the image to HPC where you can execute the image. If root authority is an issue then the answer might be a virtual environment environmen t on your laptop, like Vagrant for MacOS

    For an overview and more detailed information refer to:
    http://singularity.lbl.govSingularity Quick Start

    Here are some of the use cases we support using Singularity:

    • You already use Docker and want to run your jobs on HPC
    • You want to preserve your environment so that a system change will not affect your work
    • You need newer or different libraries than are offered on HPC systems
    • Someone else developed the workflow using a different version of linux
    • You prefer to use something other than Red Hat / CentOS, like Ubuntu 
    There are

    We have some

    tutorials located on this page

    local tutorials for Singularity


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    Matlab offers a number of free tutorials including these ones:

    Training Overview

    Machine Learning Onramp

    Deep Learning Onramp