• MDAnalysis

MDAnalysis is a python based library of tools for the analysis of molecular dynamics simulations. It is able to read and write many popular simulation formats including CHARMM, LAMMPS, GROMACS, and AMBER and more. This link contains the documentation pages of all MDAnalysis functions and has links to tutorials using Jupyter Notebooks.

• FSL Courses

This is the official University of Oxford FSL group lecture page. This includes information on upcoming and past courses (online and in-person), as well as lecture materials. Available lecture materials includes slides and recordings on using FSL, MR physics, and applications of imaging data.

• astropy

Astropy is a community-driven package that offers core functionalities needed for astrophysical computations and data analysis. From coordinate transformations to time and date handling, unit conversions, and cosmological calculations, Astropy ensures that astronomers can focus on their research without getting bogged down by the intricacies of programming. This guide walks you through practical usage of astropy from CCD data reduction to computing galactic orbits of stars.

• Docs

MediaPipe is Google's open-source framework for building multimodal (e.g., video, audio, etc.) machine learning pipelines. It is highly efficient and versatile, making it perfect for tasks like gesture recognition. This is a tutorial on how to make a custom model for gesture recognition tasks based on the Google MediaPipe API. This tutorial is specifically for video-playback, though could be generalized to image and live-video feed recognition.

• Educause HEISC-800-171 Community Group

The purpose of this group is to provide a forum to discuss NIST 800-171 compliance. Participants are encouraged to collaborate and share effective practices and resources that help higher education institutions prepare for and comply with the NIST 800-171 standard as it relates to Federal Student Aid (FSA), CMMC, DFARS, NIH, and NSF activities.

• Long Tales of Science

A series of interviews with women in the HPC community

• Data Imputation Methods for Climate Data and Mortality Data - Slices
• Github repository
• Data Imputation Methods for Climate Data and Mortality Data - Full Tutorial

This slices and videos introduced how to use K-Nearest-Neighbors method to impute climate data and how to use Bayesian Spatio-Temporal models in R-INLA to impute mortality data. The demos will be added soon.

• Warewulf Documentation

Warewulf is an operating system provisioning platform for Linux that is designed to produce secure, scalable, turnkey cluster deployments that maintain flexibility and simplicity. It can be used to setup a stateless provisioning in HPC environment.

• Pandas Docs

pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language. It lets you store data in easy to manage and display data frames, with column names and datatypes.

• NERSC Training and Tutorials Main Site
• NERSC Upcoming and Recent Training Events
• NERSC Archived Training and Tutorials

A comprehensive collection of NERSC developed training and tutorial events, offered on regular schedules. All sessions are archived, including slide decks, video recordings, and software examples as are available. Some examples of past training and tutorial topics are listed below Deep Learning for Sciences Webinar Series BerkeleyGW Tutorial Workshop VASP Trainings Timemory Software Monitoring Tutorial, April 2021 HPCToolkit to Measure and Analyzing GPU Applications Performance Tutorial Totalview Tutorial NVidia HPCSDK - OpenMP Target Offload Training Parallelware Training Series ARM Debugging and Profiling Tools Tutorial Roofline on NVIDIA GPUs GPUs for Science events 3-part OpenACC Training Series 9-part CUDA Training Series

• Overview
• Cookbook

The Biopython Tutorial and Cookbook website is a dedicated online resource for users in the field of computational biology and bioinformatics. It provides a collection of tutorials and practical examples focused on using the Biopython library. The website offers a series of tutorials that cover various aspects of Biopython, catering to users with different levels of expertise. It also includes code snippets and examples, and common solutions to common challenges in computational biology.

• Markov Decision Processes in Julia

The following link provides an easy method of implementing Markov Decision Processes (MDP) in the Julia computing language. MDPs are a class of algorithms designed to handle stochastic situations where the actor has some level of control. For example, used at a low level, MDPs can be used to control an inverted pendulum, but applied in higher level decision making the can also decide when to take evasive action in air traffic management. MDPs can also be extended to the partially observable domain to form the Partially Observable Markov Decision Process (POMDP). This link contains a wealth of information to show one can easily implement basic POMDP and MDP algorithms and apply well known online and offline solvers.

• Introduction to LSTMs

This reading will explain what a long short-term memory neural network is. LSTMs are a type of neural networks that rely on both past and present data to make decisions about future data. It relies on loops back to previous data to make such decisions. This makes LSTMs very good for predicting time-dependent behavior.

• Managing and Optimizing Your Jobs on HPC

An overview of tools and methods to manage and optimize jobs and HPC workflows

• RMACC.org

Rocky Mountain Advanced Computing Consortium Website

• Cornell's Advanced Compilers

This is a self guided online course on compilers. The topics covered throughout the course include universal compilers topics like intermediate representations, data flow, and “classic” optimizations as well as more research focusedtopics such as parallelization, just-in-time compilation, and garbage collection.

• Python Tools for Data Science

Python has become a very popular programming language and software ecosystem for work in Data Science, integrating support for data access, data processing, modeling, machine learning, and visualization. In this webinar, we will describe some of the key Python packages that have been developed to support that work, and highlight some of their capabilities. This webinar will also serve as an introduction and overview of topics addressed in two Cornell Virtual Workshop tutorials, available at https://cvw.cac.cornell.edu/pydatasci1 and https://cvw.cac.cornell.edu/pydatasci2

• Map Projections

In GIS, projections are helpful to take something plotted on a globe and convert it to a flat map that we can print or show on a screen. Unfortunately it also introduces distortions to the objects and features on the map. This not only distorts the objects visually, but the results for any spatial attribute calculations will also reflect this distortion (such as distance and area ). Below is a link to a quick primer on projections, types of distortions that can occur, and suggestions on how to choose a correct projection for your work.

• ACCESS KB Guide

Expanse at SDSC is a cluster designed by Dell and SDSC delivering 5.16 peak petaflops, and offers Composable Systems and Cloud Bursting. This documentation describes how to use the Expanse cluster with some specific information for people with ACCESS accounts.

• Trusted CI

The mission of Trusted CI is to lead in the development of an NSF Cybersecurity Ecosystem with the workforce, knowledge, processes, and cyberinfrastructure that enables trustworthy science and NSF’s vision of a nation that is a global leader in research and innovation.

• Chameleon User Guide

Chameleon is an NSF-funded testbed system for Computer Science experimentation. It is designed to be deeply reconfigurable, with a wide variety of capabilities for researching systems, networking, distributed and cluster computing and security.

• EasyBuild Documentation
• EasyConfigs Repository

EasyBuild is a software installation framework that allows administrators to easily build and install software on high-performance computing (HPC) systems. It supports a wide range of software packages, toolchains, and compilers. Supported software are found in the EasyConfigs repository, one of several resositories in EasyBuild project.

• Texas A&M Research Computing Training Resources

Training Resources and Courses offered by Texas A&M's Research Computing Group