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Current Workshop Offerings

Current Workshop Offerings


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HPC Semester Workshop Series
We would like to invite you to the HPC Seminar series this semester. We will have various topics that vary between the introduction to the HPC, basic programming, visualization, Matlab, and also the basic method to program using coprocessors.

**The seminars are free of charge and are open to cluster users or regular computer users. Registration is strongly encouraged, please click the workshop title to register.


Location: Huddle Room 539, Crawford Hall

Time: 2:00 P.M. - 3:00 P.M.

 

In keeping with the idea of RCCI's TINKERING workshops, this is a very gentle intro to working in the Command Line Interface.

We'll walk through the basics of file systems and the shell. If you have stored files on a computer at all and recognize the word “file” and either “directory” or “folder” (two common words for the same thing), you’re ready for this workshop.

If you’re already comfortable manipulating files and directories, searching for files with grep and find and writing simple loops and scripts, you probably won’t learn much from this!

You will need to bring a laptop.


Title: Visualization with GNUplot

 

Instructor: Daniel Balagué (RCCI & MAMS)

 

Location: Toepfer Room, Adelbert Hall

 

Time: 2:00 P.M. - 4:00 P.M.

 

Description: GNUplot is an open source readily available plotting tool on Windows, Linux and Mac platforms. It can be integrated into scripts easily to produce clean-looking initial graphs or high quality plots for research publications. The workshop will cover basic syntax, the basic structure of GNUPlot's data files, plotting functions and data files, and scripting.

 

Prerequisites: No previous knowledge of GNUplot is required. GNUplot is a scripting language, so being familiar with the terminal would be useful.

 

Topics:

  • Ask Gnuplot for help
  • Plot simple functions
  • Understand some of the basic options for 2D and 3D plotting
  • Understand data file structures
  • Plot different types of data files
  • Know where to find references and more examples



Title: A Crash Course in Python: Basic Structures, NumPy, and Matplotlib

 

Instructor: Daniel Balagué (RCCI & MAMS)

 

Location: Toepfer Room, Adelbert Hall

 

Time: 2:00 P.M. - 4:00 P.M.

 

Objectives: Python is a powerful multipurpose object-oriented programming language. In this workshop we will learn how Python could be an easy replacement to Matlab or Mathematica in certain situations. We will learn the basics of the Python language and its data structures; how to optimize numerical computations using NumPy: "the library for high performance scientific computing"; the concept of "vectorization"; and how to create figures using the Matplotlib library.

 

Prerequisites: No Python knowledge required (but the audience is expected to have some basic programming experience). Have a Python distribution installed (the "anaconda2" Python distribution is recommended https://www.continuum.io/downloads).

 

Topics:

  • Basic Python: indentation, functions control flow
  • Python Structures: Lists, Tuples, Sets, Dictionaries
  • Basic Numpy: a Python library for high performance scientific computing (multidimensional arrays, vectorization, and linear algebra)
  • Basic Matplotlib: a powerful Python library for visualizing data



Location: Toepfer Room, Adelbert Hall

Time: 2:00 P.M. - 4:00 P.M.

Advancing: Matlab I. The first of three courses that will take new users from the introduction up to tackling programming/profiling, and complex parallel jobs
•    Intended audience: HPC Users.
•    Basic prerequisites: A laptop with access to the HPC cluster.
•    Learning outcomes: Learn how to run both serial and parallel MATLAB jobs in HPC; know about licenses and memory management; Debugging, Profiling & Benchmarking, and MATLAB Compiler & Coder.


Location: Toepfer Room, Adelbert Hall

Time: 2:00 P.M. - 4:00 P.M.

 

This short workshop would introduce the HPC cluster users to the new Rider cluster that is based on Red Hat Enterprise Linux (RHEL) 7 and some of the subtle differences with the current RedCat cluster that is based on RHEL6.

  • Intended audience: current cluster users or potential cluster users with some knowledge about running jobs in the current cluster.
  • Learning objectives: for the users to be familiar with the new Rider cluster, with the different login and cluster setup, basic changes in the module environment setup, installed libraries, and jobs workflow.



Location: Toepfer Room, Adelbert Hall

Time: 2:00 P.M. - 4:00 P.M.

Location: Huddle Room 539, Crawford Hall

Time: 2:00 P.M. - 3:00 P.M.

Location: Room 206, Clark Hall

Time: 1:00 P.M. - 2:00 P.M.

The Exploring TEI Workshop is an opportunity for participants to learn more about the Text Encoding Initiative (TEI) from knowledgable TEI Practitioners. As with all Exploring workshops offered by Research Computing, this is a tech-free offering. For more on RCCI's new workshop structure, visit https://case.edu/utech/research-computing/training/

Session 1 - Oct 20 - Constance Crompton will discuss the use of TEI as a tool for digital projects and a vehicle for digital publication of scholarly materials.

Session 2 - Oct 27 - Diane Jakacki will discuss TEI's uses in the classroom as a pedagogical tool.

Location: Huddle Room 539, Crawford Hall

Time: 2:00 P.M. - 3:00 P.M.

As with other RCCI "Tinkering" courses, this is a very gentle, hands-on intro to Regular Expressions (RegEx). RegEx is *very* powerful -- we'll be just dipping our toes in!

‌‌Session 1 - Instructor: Tianna Uchacz

Location: Room 206, Clark Hall

Time: 12:00 P.M. - 1:00 P.M.

Wednesday, October 11, 2017 - Register Here


Session 2 - Instructor: Virginia Kuhn

Location: Room 206, Clark Hall

Time: 12:00 P.M. - 1:00 P.M.

Wednesday, October 25, 2017 - Register Here


Session 3 - Instructor: Tassie Gniady

Location: Room 206, Clark Hall

Time: 12:00 P.M. - 1:00 P.M.

Wednesday, November 8, 2017 - Register Here


Session 4 - Instructor: Karen Monsen

Location: Room 206, Clark Hall

Time: 12:00 P.M. - 1:00 P.M.

Wednesday, November 22, 2017 - Register Here


Big Data isn't just about numbers! It might not even be particularly big (in terms of storage size). Many disciplines that traditionally use 'big data' study large, existing datasets or data generated via research study or clinical information. However, students and faculty in English, History, Classics or Law may be interested in querying larger portions of the total textual product of humankind, a dataset of thousands of texts rather than dozens. Statisticians or political scientists interested in several decades worth of aggregated insurance information, voting records or medical information (textual or image-based).

Regardless of the field of study of the nature of your data, computational approaches to analysis can radically change your perspective of your data by providing access to and analysis of a far larger set of data than would be possible without computer assistance.

These sessions will be a tech-free introduction to 'Big Data' topics in fields that may not traditionally have used computational methodologies. There will be four lunchtime meetings during the Fall semester. Lunch will be provided. Registration is required.



Description of Workshops

For information on our newly designed workshop structure, visit the Training Structure + Details page.

Basic Tutorials

  • Working: Basic Linux.This workshop goes through the reason why HPC uses Linux, explains the kernel, the shell, the files and the commands.

    • Intended audience: students and Faculty who have (almost) no knowledge on how to use a Linux/Unix terminal

    • Basic prerequisites: basic computing knowledge

    • Learning outcomes: learn how to navigate on a Linux/Unix system: folder structure, understand user permissions, create folders, move files, transfer files from local machine to a remote machine, using less to visualize files, using pipes, etc.

  •  Level 3.1 
  • Advancing: HPC Module System and Slurm Scheduler. This introduction to HPC invites new users to quickly run jobs on the cluster

    • Intended audience: HPC users.

    • Basic prerequisites: Basic Linux/Unix.

    • Learning outcomes: understand the module system and know how to use it. Understand how to allocate the right resources and how to write a Slurm script. 

  • Advancing: Shell Scripting. Shell language can be combined with the Slurm commands to submit multiple jobs to the cluster queue while changing the input parameters accordingly (or job arrays)

    • Intended audience: users of the HPC who could take advantage of shell scripting when writing Slurm scripts, other faculty, students, and staff who want to learn how to create a shell script.

    • Basic prerequisites: have basic experience with Unix/Linux or have attended the "Basic Linux/Unix Shell" workshop.

    • Learning outcomes: learn how to code a shell script. 

  • Level 3.2 

  • Advancing: Visualization with GNUPlot. GNUplot is an open source readily available plotting tool on Windows, Linux and Mac platforms. It can be integrated into scripts easily to produce clean-looking initial graphs or high quality plots for research publications.

    • Intended audience: anyone who wants to use GNUPlot as a Visualization tool.

    • Basic prerequisites: a laptop with GNUPlot installed.

    • Learning outcomes: understand the basic structure of GNUPlot's data files. Learn the basic syntax. Learn how to plot functions and data files. Scripting.  

  • Level 3.3 

  • Advancing: R -- Introduction, Visualization, Use-cases. This introduction gives an array of possibilities when using R and emphasizes why R is a selected environment choice for many people.

    • Intended audience: anyone who wants to get started with R Statistics

    • Basic prerequisites: a laptop with R installed.

    • Learning outcomes: Learn the basic syntax of R, R Packages, Visualization.

  • Advancing: Matlab I. The first of three courses that will take new users from the introduction up to tackling programming/profiling, and complex parallel jobs

    • Intended audience: HPC Users.

    • Basic prerequisites: a laptop with access to the HPC cluster.

    • Learning outcomes: learn how to run both serial and parallel job in HPC; know about licnese and memory management; Debugging, Profiling, and Benchmarking; MATLAB Compiler & Coder.

 

  • Level 4.1 

  • Mastering: Software Installation on the HPC cluster -- Python Modules, R Modules, and Compilation. This course introduces basic installation to new users, starting from copying/installing the binaries locally, add packages in R or Python, as well as a simple configure-make-make install sequence.

    • Intended audience: HPC users.

    • Basic prerequisites: basic Linux/Unix, Shell Scripting, and access to the HPC cluster.

    • Learning outcomes: learn how to install locally a Python or R module that a user may need. Learn how to compile software and install it on your home folder for personal use. 

  • Level 4.2 

    • Mastering: Parallel programming -- OpenMP. This workshop teaches advanced programmers in C/C++ or Fortran some techniques to speed up their codes using OpenMP.

      • Intended audience: HPC users and other C/C++ or Fortran programmers who can make use of parallel programming to speed up their code.

      • Basic prerequisites: C/C++ or Fortran programing experience.

      • Learning outcomes: identify shared and private variables for a parallel for loop. Understand how to parallelize a loop effectively. Simplify or refactor code using reductions, identify independent operations that could run in parallel, run parallel code on the HPCC.