Every month, the PACE team offers a variety of events to help expand the computational skillset of researchers using our resources. Additionally, we frequently partner with major research institutions and other external groups to hold workshops for Georgia Tech students, staff, and faculty.
The following workshops are currently offered:
Workshops and Trainings
PACE Clusters Orientation
PACE Clusters Orientation provides new or existing users with the fundamental information needed to get started using PACE clusters, including Phoenix, Hive, and Firebird. We strongly encourage all PACE users to attend at least one of these classes. To make Orientation accessible to the broadest audience, it is offered in both live interactive sessions and in a series of recorded videos. Learn more and register for an Orientation session
Applications of Machine Learning
Actually doing your first Machine Learning project can be challenging: How to handle the data? How to identify what is important in the data? How to visualize correlations? How to evaluate your model? How to avoid some common pitfalls? In this workshop, we will work-through a first project in machine learning. We will begin with a concept of a project (detection of breast cancer), ingest the data, visualize and view potential correlations, select, train our model, and evaluate the model. Learn more and register for Applications of Machine Learning
Collaborative Event: XSEDE/ACCESS HPC Workshops for Large Scale and/or Machine Learning Workflows
PACE frequently hosts HPC Workshops offered by the Pittsburgh Supercomputing Center through ACCESS (and formerly through XSEDE). Videos of past sessions are available on their YouTube channel. Visit to learn about MPI, OpenMP, GPU Programming using OpenACC, and Big Data and Machine Learning.
Linux 101
This is an introductory course to Linux. It is recommended for anyone new to the Linux environment, especially if you are a PACE user. Learn more and register for Linux 101
Linux 102
Building upon the content of PACE – Linux 101, this monthly class is designed to extend the command-line capabilities of PACE users so that they can more efficiently address computational research in a Linux environment. After taking this class, users will be able to demonstrate their ability to utilize regular expressions for stream manipulation with tools like sed and awk, compile code from source with version control and build utilities such as git and make, implement advanced I/O manipulation for in-situ processing, and integrate advanced compression with system tools for better data management. Learn more and register for Linux 102
Git 101
Get control of your source code by using a version control system. In this course, we’ll learn how to use Git to manage changes to your source code so that you can track updates and rollback to a previous version in case something breaks. We’ll start by learning to use git to create a local personal repository, adding new files, and committing updates. We’ll then learn how to host your repository on the GT github server so that others can collaborate and so that you can synchronize the software across different, remote machines. Learn more and register for Git 101
Optimization 101
This course will include benchmarking, profiling, and optimization a serial linear algebra problem. We will use a problem-directed approach, focusing on matrix multiplication in the context of systems of linear equations solvers.
The course is recommended for researchers with a background in compiled languages such as C/C++ or Fortran. Learn more and register for Optimization 101
Python 101: Intro to Data Analysis with NumPy
PACE’s Python 101: Intro to Data Analysis with NumPy introduces PACE users to analyzing scientific and engineering data using Python in a Hands-On course.
Instruction focuses on basic Python skills and key features of the NumPy and Matplotlib libraries through a data analysis example. The course is taught through a Jupyter Notebook, and participants will have multiple opportunities for hands-on exercises throughout the session. The workshop will also cover the mechanics of setting up a Jupyter Notebook on the PACE cluster.
This course is recommended for anyone new to Python and NumPy, especially if you are a PACE user. Learn more and register for Python 101: Intro to Data Analysis with NumPy
ICE Orientation
ICE Orientation is required for all faculty and TAs assisting with a course using ICE. Learn more about ICE
Slurm Orientation
PACE Slurm Orientation provides researchers with fundamental information about using the Slurm scheduler. We encourage all PACE researchers to attend as all of our HPC clusters use Slurm. Learn more and register for Slurm Orientation
OSG Orientation
PACE’s OSG and OSPool Orientation introduces the Georgia Tech researchers to the Open Science Grid (OSG) and the distributed High Throughput Computing resources available to all researchers at all US institutions at no charge via the Open Science Pool (OSPool). Learn more and register for OSG Orientation
Weekly No-cost Consultation Sessions
PACE provides weekly no-cost consultation sessions to help users get up and running on PACE systems. Sessions rotate between Tuesdays and Thursdays.