NCSA Training and Seminars

5 matches found

    • 3:00 - 4:00 pm    4/2/2025
    • Electrical and Computer Engineering Room: 1013

    This Seminar covers topics on building and training ML models, ranging from beginner to complex, deep learning models trained on the Delta Supercomputer's multi-GPU nodes. This seminar is open to all, including graduate students, undergrads, and particularly domain scientists whose primary affiliation is not with a STEM program or department.

    • 10:00 am - 4:00 pm   Central Time    4/9/2025
    • NCSA Room 3000

    Attend this onsite workshop at NCSA to learn how to use OpenACC API compiler directives to quickly develop GPU-capable codes using standard languages and compilers. Knowledge of either C or Fortran programming is required. Hands-on exercises will use Pittsburgh Supercomputing Center’s Bridges-2 computing platform.

    • 3:00 - 4:00 pm    4/9/2025
    • Electrical and Computer Engineering Room: 1013

    This Seminar covers topics on building and training ML models, ranging from beginner to complex, deep learning models trained on the Delta Supercomputer's multi-GPU nodes. This seminar is open to all, including graduate students, undergrads, and particularly domain scientists whose primary affiliation is not with a STEM program or department.

    • 3:00 - 4:00 pm    4/16/2025
    • Electrical and Computer Engineering Room: 1013

    This Seminar covers topics on building and training ML models, ranging from beginner to complex, deep learning models trained on the Delta Supercomputer's multi-GPU nodes. This seminar is open to all, including graduate students, undergrads, and particularly domain scientists whose primary affiliation is not with a STEM program or department.

    • 3:00 - 4:00 pm    4/23/2025
    • Electrical and Computer Engineering Room: 1013

    This Seminar covers topics on building and training ML models, ranging from beginner to complex, deep learning models trained on the Delta Supercomputer's multi-GPU nodes. This seminar is open to all, including graduate students, undergrads, and particularly domain scientists whose primary affiliation is not with a STEM program or department.