Training and Events

From hands-on workshops to interactive webinars, we host a variety of events designed to educate our users on the tools, systems, and frameworks that are available to accelerate their scientific computing projects.

Upcoming
Past

Argonne National Laboratory
Building 240/Room 4301

Promising Frontiers in Approximation Techniques for Mixed-Integer Optimal Control

  • Paul Manns, Technical University of Braunschweig

Argonne National Laboratory
Building 240/Room 1405

Principles of Open Government Data and Open Science in Archaeology: Big Data Lessons from the Digital Index of North American Archaeology (DINAA)

  • Joshua Wells, Indiana University South Bend
Shutterstock image

Argonne National Laboratory
Building 240/Room 4301

The Critical Need for High Performance Computing Network Simulation Capabilities: The PETSc DMNetwork Approach

  • Getnet Betrie, Argonne National Laboratory

Argonne National Laboratory
Building 240/Room 4301

Scientific Machine Learning: Learning from Small Data

  • Lu Lu, Brown University

Argonne National Laboratory
Building 240/Room 1404-1405

Inference of Uncertain Parameters in Physical Models Governed by PDEs with Application to Earth's Mantle Convection

  • Johann Rudi, Argonne National Laboratory
image is a schematic of Earth interior and some magnetic field lines from a model

Argonne National Laboratory
Building 240/Room 1404

Role of Nonlocal Operators in Inverse Problems and Deep Learning

  • Ratna Khatri, George Mason University

Argonne National Laboratory
Building 240/Room 4301

Deep Belief Network for Classification and Hierarchical Classification of Images

  • Jaehoon Koo, Northwestern University

Argonne National Laboratory
Building 240/Room 4301

The Proxy Point Method for Rank-Structured Matrices

  • Xin Xing, Georgia Institute of Technology
Shutterstock image

Online

Type Webinar

Profiling Application Performance Using Intel Vtune and Advisor

  • Paulius Velesko, Intel
Jan2020 Dev Session

Argonne National Laboratory
Building 240/Room 1404

How Deep Learning and Life Science Could Advance Each Other

  • Liang Zhao, George Mason University
Shutterstock image

Argonne National Laboratory
Building 240/Room 1406-1407

Practical Random Sketching

  • Vivak Patel, University of Wisconsin-Madison

Houston, Texas
Royal Sonesta Houston Galleria

2020 Exascale Computing Project Annual Meeting

ECP Logo

Argonne National Laboratory
Building 240/Room 1404-1405

Type Lecture
Level Advanced

Investigating Quasi-Newton Outer Product Representations on GPUs

  • Alp Dener, Argonne National Laboratory

Argonne National Laboratory
Building 240/Room 1416

GPUs, Why They Are So Important, and Why Everyone Hates Them

  • Barry Smith, MCS
Quantum information science grant

Argonne National Laboratory
Building 240/Room 4301

Quantum Machine Learning Using Kernels

  • Matthew Otten, Maria Goeppert Mayer Fellowship - Argonne Scholar, NST/ANL
Quantum machine learning

Argonne National Laboratory
Building 240/Room 1416

Type Workshop

Aurora ESP Workshop: TWO

  • Intel and ALCF Staff
Aurora ESP

Argonne National Laboratory
Building 240/Room 1404-1405

Accurate and Efficient Methods for Reduced-Complexity Modeling in Fluid Mechanics

  • Scott Dawson, Illinois Institute of Technology

Argonne National Laboratory
Building 240/Room 4301

Computer Model Calibration Using a Deep Neural Network

  • Won Chang, University of Cincinnati
DOE supercomputer

Kansas City, MO
InterContinental Kansas City at the Plaza

Type Workshop

Performance, Portability, and Productivity in HPC Forum

2020 Performance, Portability, and Productivity in HPC Forum

Argonne National Laboratory
Building 240/Room 4301

Ecosystem Services Provided by Shrub Willow Buffers in a Row Crop Production System

  • Colleen Zumpf, University of Illinois Urbana-Champaign
Shutterstock image

Argonne National Laboratory
Building 240/Room 4301

Fault Detection and Location in Multi-Terminal dc (MTdc) Systems

  • Bhaskar Mitra, University of North Carolina at Charlotte
detect

Online Video

Type Webinar

ALCF Getting Started on Theta

  • ALCF Staff
Getting Started on Theta

Refactoring EXAALT MD for Emerging Architectures

  • Aidan Thompson, Sandia National Laboratories
  • Stan Moore, Sandia National Laboratories
  • Rahulkumar Gayatri, NERSC

Fermilab
Wilson Hall, Curia II

Computational Science Seminar Series: AI for Science at Argonne

  • Ian Foster, Argonne National Laboratory

Argonne National Laboratory
Building 240/Room 4301

Light-Weight Performance Analysis for Next-Generation HPC Systems

  • Jidong Zhai, Tsinghua University
2020 Performance, Portability, and Productivity in HPC Forum

Argonne National Laboratory
Building 240/Room 1404

Efficient Interoperability between Parallel Libraries

  • Poornima Nookla

Argonne National Laboratory
Building 240/Room 1404-1405

Partitioning a Large Simulation as It Runs

  • Kary Myers, Los Alamos National Laboratory

Argonne National Laboratory
Building 240/Room 4301

Unit Commitment with Gas Network Awareness

  • Geunyeong Byeon, University of Michigan

Argonne National Laboratory
Webinar

Type Webinar

Leveraging Physical Models in Machine Learning

  • Rebecca Willett, University of Chicago

Argonne National Laboratory
Building 240/Room 4301

Type Lecture

Distributionally Robust Transmission Grid under Geomagnetic Disturbances

  • Minseok Ryu, University of Michigan

Online

Type Webinar
Level General

An Overview of Aurora, Argonne's Upcoming Exascale System

  • Colleen Bertoni, Argonne National Laboratory
  • Sudheer Chunduri, Argonne National Laboratory
ALCF Developer Sessions

Argonne National Laboratory
Building 240/Room 4301

Type Lecture
Level Advanced

Mixed-Integer PDE-Constrained Optimization

  • Sven Leyffer, Argonne National Laboratory

Argonne National Laboratory
Building 240/Room 4301

Autotuning under Tight Budget Constraints: A Transparent Experimental Design Approach

  • Pedro Bruel, University of Grenoble Alpes

Argonne National Laboratory
Building 240/Room 4301

Robust Optimization with Variable Uncertainty

  • Kartikey Sharma, Northwestern University

Argonne National Laboratory
Building 240/Room 1416

Type Lecture
Level Advanced

Scientific Deep Learning: Reproducibility, Interpretability & Uncertainty Quantification

  • Elise Jennings, Argonne National Laboratory

Argonne National Laboratory
Building 240/Room 4301

Type Lecture
Level Advanced

Adjoints in Boundary Integrals Constrained Optimization

  • Oana Marin, Argonne National Laboratory

Argonne National Laboratory
Building 446 Auditorium

Type Lecture

Using Machine Learning To Predict Facets of Antimicrobial Resistance

  • Jim Davis, Argonne National Laboratory

Argonne National Laboratory
Building 240/Room 4301

Type Lecture
Level Advanced

Practical Optimization on Near-term Quantum Computers

  • Ruslan Shaydulin, Clemson University

Argonne National Laboratory
Building 240/Room 4301

Type Lecture

Numerical Stability of Interface Conditions for Ocean-Atmosphere Coupling

  • Hong Zhang, MCS