NCSAatIllinois

CAII 10/18 Fall Seminar Featuring Illinois CS Professor Bo Li

Graph Engine to Tackle the Toughest Graph Analytics Challenges

Type Ia Supernovae

AMDs EPYC Architecture and Programming Environment on Delta

Tutorial: Python Best Practices on Blue Waters -- Colin Maclean, NCSA

Using the NVIDIA Software Ecosystem on the NVIDIA Ampere A100 and A40 GPUs

The Hepatitis B Capsid through the Computational Microscope - Jodi Hadden

Getting Started with HAL

Numerical Relativity and the Binary Black Hole Problem — Miguel Alcubierre

CAII HAL Training: Data Loaders (William Eustis)

The Mechanism of the Sarco/Endoplasmic Reticulum ATP-Driven Calcium Pump

CAII HAL Training: How to Use Pre-Trained Models

NCSA Industry: Crafting Solutions for Grand Challenges

CAII HAL Training: Introductions to Machine Learning and Neural Networks (Aaron Saxton)

Introduction to PyTorch

The Semileptonic Kaon Decay Form Factor at the Physical Point

Tutorial: "Machine Learning with Python: Distributed Training and Data Resources on Blue Waters"

XAI Tutorial: Explainability OF Deep Neural Networks

Introduction to PyTorch

Robust Physics-Informed Neural Networks

Introduction to TensorFlow

From Megaflop to Petaflop and Beyond

From NCSA to the National Research Platform - Dr. Larry Smarr

Visualization of Hurricane Michael

CAII HAL Training: Introduction to PyTorch (Priyam Mazumdar)

Simulation and Visual Representation of Tropical Cyclone-Ocean Interactions

CAII HAL Training: Getting Started with HAL (Volodymyr Kindratenko)

Hydroclimate of South America Visualization

NCSA. More Than Ready.

Automated Detection of Disease Using Expressive Human Signals (Dr. Mary Pietrowicz)

NCSA Cybersecurity Best Practices for K–12 Teachers

How to Use Pretrained Models

Introduction to TensorFlow

Kepler Scientific Workflow System

Visualization of a Tornado-Producing Thunderstorm

Introduction to Transformers Models

Getting Started on NCSA's Delta Supercomputer

Distributed Data Parallel Model Training in PyTorch

NCSA. More Than CPUs.

Scientific Software Ecosystems: Why and How

How supercomputers and visualization can help the global food crisis

Welcome/Introduction -- Bill Kramer, NCSA/University of Illinois at Urbana-Champaign

Applying Data Science in Business

Introduction to Parallel Computing on High-Performance Systems

Don Wuebbles: Particulate Matter Prediction and Source Attribution for U.S. Air Quality ...

DRYML an Open Source Meta-Library for Machine Learning and More

Visualizing Non-Spatial Data

NCSA b-roll video: Blue Waters supercomputer

Developing Interactive Parallel Workflows in Python using Parsl

Supercomputing in an Era of Big Data and Big Collaboration

NCSA. More Than You Expect.