The ALCF provides users with access to supercomputing resources that are significantly more powerful than systems typically used for open scientific research.
The ALCF is accelerating scientific discoveries in many disciplines, ranging from chemistry and engineering to physics and materials science.
The ALCF is committed to providing training and outreach opportunities that prepare researchers to efficiently use its leadership computing systems, while also cultivating a diverse and skilled HPC workforce for the future.
The Argonne Leadership Computing Facility enables breakthroughs in science and engineering by providing supercomputing resources and expertise to the research community.
The ALCF Support Center assists users with support requests related to their ALCF projects.
Help Desk Hours: 9:00am-5:00pm CT M-F Email: support@alcf.anl.gov
Access archived presentations and other materials from past ALCF training events below.
Type Slides System Aurora Published 01/25/2023
SYCL is becoming a de facto standard for vendor agnostic heterogeneous computing. Upgrading CUDA code to standard C++ with SYCL makes the applications portable across a range of existing and evolving...
Type Slides System Polaris Published 12/07/2022
As long as humans write software, there will be software bugs. And as many computational scientists today are orchestrating thousands of threads across massively parallel GPU systems, debugging and...
Type Video Published 11/09/2022
In this workshop, we will explore Intel(r) Extensions for Scikit-Learn*. See how to leverage optimizations for common machine learning tools in Scikit-Learn. In this hands-on lab, we explore Intel(r)...
Type Video Published 11/08/2022
The series will wrap up with a demo on the ALCF AI testbed and an introduction to the wider toolset of AI methods.
Dr. Vázquez-Mayagoitia will also giving a science talk on the impact of machine...
Type Slides Published 11/08/2022
Type Slides Published 11/01/2022
Trainees will combine data pipeline and parallel training from previous sessions to train a modern classification network on a supercomputer.
Dr. Eliu Huerta will also speak about the work he does at...
Type Video Published 11/01/2022
Type Slides System Aurora Published 10/26/2022
Abstract:
Scikit-learn is among the most useful and robust libraries for machine learning, providing a selection of tools for ML and statistical modeling via a consistent interface in Python...
Scikit-learn is among the most useful and robust libraries for machine learning, providing a selection of tools for ML and statistical modeling via a consistent interface in Python, including...
Type Slides Published 10/25/2022
Type Video Published 10/25/2022
Type Video Published 10/18/2022
Type Slides Published 10/18/2022
Type Video Published 10/11/2022
Type Slides Topic Data Science System AI Testbed Published 10/06/2022
As part of the 2022 ALCF Simulation, Data, and Learning Workshop
Type Slides Topic Data Science System Polaris Published 10/06/2022
As a part of the 2022 ALCF Simulation, Data, and Learning Workshop
Type Slides System Aurora Published 10/06/2022
Type Slides Topic Account and Project Management System Polaris System ThetaGPU System Theta Published 10/06/2022