Knowledge Base Resources

Landing Page for Bridges-2 information

An introduction to Cloud Computing

The Neuroimaging Tools and Resources Collaboratory (NITRC) is a neuroimaging informatics knowledge environment for MR, PET/SPECT, CT, EEG/MEG, optical imaging, clinical neuroinformatics, imaging genomics, and computational neuroscience tools and resources.

Thrust is a CUDA library that optimizes parallelization on the GPU for you. The Thrust tutorial is great for beginners. The documentation is helpful for anyone using Thrust.

VSCode is a popular IDE that runs on Windows, MacOS, and Linux. This tutorial will explain how to get set up with VSCode to code in Python. It will also provide a tutorial on how to set up Github integration within VSCode.

The free online book for the mlr3 machine learning framework for R. Gives a comprehensive overview of the package and ecosystem, suitable from beginners to experts. You'll learn how to build and evaluate machine learning models, build complex machine learning pipelines, tune their performance automatically, and explain how machine learning models arrive at their predictions.

As LLMs get larger fine-tuning to the full extent can become difficult to train on consumer hardware. Storing and deploying these tuned models can also be quite expensive and difficult to store. With PEFT (parameter -efficent fine tuning), it approaches fine-tune on a smaller scale of model parameters while freezing most parameters of the pretrained LLMs. Basically it is providing full performance that which is similar if not better than full fine tuning while only having a small number of trainable parameters. This source explains that as well as going over LORA diagrams and a code walk through.

There is a detailed explanation about communication routines and managing methods of different MPI libraries, as well as several exercises designed for users to get familiar with the implementation of MPI build process.

This presentation gives a detailed breakdown of the outcome of my master's thesis which was focused on making HPC Clusters accessible across all disciplines in a university setting "Our Case Study was the university of Cincinnati".

The realm of data science is one that onlookers regard with curiosity and respect. There are a lot of unknowns in this area of study that only recently became hugely relevant. It is important to get the facts on how expertise in data science is transforming the world. This article features what a bachelor’s degree means in today’s market and the future.

A couple of resources that: 1.) Presents and defends a git branching workflow for stable collaborative git based projects. ("A Successful Git Branching Model") 2.) Maps "What do you want to do?" to the commands necessary to accomplish it. ("Git Flight Rules")

InsideHPC is an informational site offers videos, research papers, articles, and other resources focused on machine learning and quantum computing among other topics within high performance computing.

This workshop has an introduction to the concepts of visualization followed by hands on exercises. The concepts section has Speaker Notes, and the hands on section has an accompanying Jupyter notebook. The workshop is one in a series of Introduction to HPC

Data visualization is a critical aspect of data analysis. It allows for a clear and concise representation of data, making it easier for users to understand and interpret complex datasets. One of the most popular libraries for data visualization in Python is Matplotlib. The included website aims to provide a brief overview of Matplotlib, its features, and examples/exercises to dive deeper into its functionalities.

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

This tutorial introduces the use of Containers using the Charliecloud software suite. This tutorial will provide participants with background and hands-on experience to use basic Charliecloud containers for HPC applications. We discuss what containers are, why they matter for HPC, and how they work. We'll give an overview of Charliecloud, the unprivileged container solution from Los Alamos National Laboratory's HPC Division. Students will learn how to build toy containers and containerize real HPC applications, and then run them on a cluster. Exercises are demonstrated using the ACES cluster, a composable accelerator testbed at Texas A&M University. Students with an allocation on the ACES cluster can follow along with the ACES-specific exercises.

Representation learning is a fundamental concept in machine learning and artificial intelligence, particularly in the field of deep learning. At its core, representation learning involves the process of transforming raw data into a form that is more suitable for a specific task or learning objective. This transformation aims to extract meaningful and informative features or representations from the data, which can then be used for various tasks like classification, clustering, regression, and more.

5 Days of recordings of Python data analysis and visualization training.

Resources and User Guide available at Rockfish

Gaussian 16 is a computational chemistry package that is used in predicting molecular properties and understanding molecular behavior at a quantum mechanical level.

HPCwire is a prominent news and information source for the HPC community. Their website offers articles, analysis, and reports on HPC technologies, applications, and industry trends.

This tutorial will give you an introduction to neural networks using the ever-famous MNIST handwritten digits database! Presented by Robin Hwang.

VisIt is a prominent open-source, interactive parallel visualization and graphical analysis tool predominantly used for viewing scientific data. Its GitHub repository offers a detailed insight into the software's source code, documentation, and contribution guidelines. In particular, it offers useful examples on how it

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