Education & Resources
CARC's Research Facilitation & Applications team offers a number of workshops designed to introduce users to CARC systems, as well as workshops on using specific software and programming languages in a high-performance computing environment.
The workshops below are approximately two hours in length and are offered several times a year on a rotating basis. Stay up to date on upcoming workshops by checking the schedule below and subscribing to the monthly CARC newsletter.
Due to the ongoing COVID-19 pandemic, all workshops are currently being hosted via Zoom.
Recordings of the workshops can be accessed at Video Learning or on CARC's YouTube channel.
If you are interested in attending one of our workshops but you do not already have a CARC account, please submit a help ticket before registering and we can create an account for you.
Research computing essentials
Introduction to Research Computing on CARC Discovery Cluster
An overview of CARC's services and high-performance computing clusters, including how to log in, manage and transfer data, load and build software, and run and monitor jobs.
CARC OnDemand: Scientific Computing on CARC from a Web Browser
This workshop is offered as a pre-recorded video only. Open OnDemand allows users to access CARC resources from within a web browser. This presentation will discuss how to manage files, getting shell access, running jobs, and how to start interactive apps with a graphical interface.
Introduction to Linux
This workshop is offered as a pre-recorded video only. An introduction to Linux that covers the basic skills needed to be productive in a command-line environment on Unix-like systems such as CARC's high-performance computing clusters. Topics include an overview of the Linux operating system, how to run commands, navigate file systems, create and edit files, use pipes and filters, and develop shell scripts.
Installing and Using Software on CARC Systems
An overview of the software stacks available on CARC systems, using the Lmod software module system. Topics include how to find and load modules, manage your shell environment, build your own software, and create your own modules.
Running Jobs on CARC Systems
An overview of job submission and monitoring using the Slurm workload manager and job scheduler. Topics include cluster and node information, resource requests, job history and efficiency, job dependencies, and job arrays.
Scientific Computing Series
This two-part series introduces the concepts and tools that are essential for high-performance computing through a combination of lectures and hands-on practices.
Overview of an HPC Cluster and Essential Linnux Commands
In the first part, we start with getting to know CARC’s HPC ecosystem and discussing the basic Linux shell commands, then we continue with a brief introduction to python and writing our first program with it. This is followed by discussing the need for version control and setting up your Github repository.
Parallel Processing with MPI in Python
In this next section, we cover the fundamental concepts involved in developing a parallel program using Massage Passing Interface in Python via the mpi4py package. The essential concepts are introduced using hands on tutorials.
Advanced topics in research computing
Software Containers with Singularity
An overview of software containers and using Singularity to create and run containers for high-performance computing tasks.
Running Deep Learning Applications on HPC Systems
This workshop is an advanced course on Python with specific emphasis on running deep learning applications on HPC systems.
Introduction to Python
An introduction to the Python programming language. This workshop covers basic Python syntax, installing and importing packages, visualizing data, and writing scripts.
HPC Using Python
Intermediate-to-advanced topics for getting improved Python performance in an HPC cluster environment. Covers debugging, profiling, and parallel programming.
Introduction to R
An introduction to the R programming environment and language for statistical computing and graphics. Topics include base R and packages, objects and functions, importing and exporting data, summarizing data, visualizing data, modeling data, control flow, iteration, and scripting.
HPC Using R
An intermediate-to-advanced workshop on HPC methods in R programming. Topics include profiling and benchmarking, vectorizing code, memory use, data I/O, and parallel programming. Assumes basic proficiency in R programming.
Introduction to Julia
An introduction to the Julia programming language for scientific and technical computing. Topics include base Julia and packages, data types and structures, functions, control flow, iteration, and scripting.
HPC Using Julia
An intermediate-to-advanced workshop on HPC methods in Julia programming. Topics include profiling and benchmarking, memory use, data I/O, and parallel programming. Assumes basic proficiency in Julia programming.
Introduction to Cloud Computing on AWS
The goal of this workshop is to introduce the concept of cloud computing, focusing on the main elements of the HPC workflow. The practice materials are presented based on the AWS products, however similar concepts can be adopted to other major cloud service providers.
Basic concepts such as regions, zones, VPC, and subnets are explained. Different machine types, as well as storage options are briefly described and the possible use cases for each type are discussed.
Creating a Virtual Machine on USC's Artemis Cloud
In this workshop, we will discuss the different elements of an HPC cluster in the cloud and how to select the different components involved in creating a scalable cluster. The attendees are strongly encouraged to attend the previous workshop on the basics of cloud computing on AWS.
Building Neural Networks for Deep Learning Applications
This workshop is an advanced course. It will cover basis of neural networks and how to write code in Pytorch to build deep neural networks.
Data Analysis and Visualization Using Panda and Matplotlib
This workshop is an intermediate course on Python with specific emphasis on data analysis and visualization. It will cover the use of Panda and Matplotlib, popular libraries for data processing, manipulation, and visualization.
Computational Biology on CARC Systems
An overview of CARC's computational biology resources and tools, including demonstrations of common use cases.
Density Functional Theory Methods Using Quantum Espresso [series]
This workshop series will benefit researchers who are interested in or are starting to learn about the application of theoretical methods and techniques for the study of the physics and chemistry of the solid state. These hands-on oriented workshops are targeted towards undergraduate, graduate, and post-doctoral students who wish to use Density Functional Theory (DFT) methods in their research. The aim is to teach the basics of ab initio atomistic materials simulation using the Quantum Espresso (QE) plane-wave pseudopotential software suite. The workshops will consist of lectures, demonstrations, and practical hands-on sessions using the Discovery HPC cluster.
CP2K: Atomistic Simulations [series]
CP2K is a suite of modules for electronic structure and molecular dynamics simulations optimally suited for the simulation of complex condensed phase systems and materials. This workshop provides an introduction to the most relevant computational tools implemented within the CP2K program package to researchers and students in the field of molecular simulations. This workshop focuses on methodologies available in CP2K and encourages modular, flexible, and problem-oriented thinking while using them. The most standard methods as well as some of the more advanced features will be introduced by overviews of background theory and through examples of application, always related to the specific implementation in this code. Recurring topics in the workshop are the scaling of algorithms, the combination of different levels of theory and of sampling, and tools and strategies for the analysis of results.
Topics covered include:
- Kohn-Sham density functional methods using the Gaussian and Plane Wave (GPW) and the Gaussian Augmented Plane Wave (GAPW) methods
- Ab initio molecular dynamics and enhanced sampling methods
- Advanced electronic structure methods and electronic properties
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