In This Message

Meetings & Workshops
– AI Training Series: AI for Science at Scale – Introduction (June 15)
– AI Training Series: SmartSim at OLCF (July 13)
Upcoming Downtimes
– Frontier (June 06)
– Marble (June 13)
Center Announcements
– OLCF Office Hours Sign-up is now available in myOLCF
– May 2023 OLCF User Conference Call – OLCF Storage

Meeting & Workshops

AI Training Series: AI for Science at Scale – Introduction
June 15, 1:00 pm – 3:00 pm EDT

Machine learning (ML) is a subset of Artificial Intelligence (AI) that uses statistical learning algorithms to build applications that can automatically learn and improve from its experiences. Deep learning (DL) is a subset of ML that is inspired by the way a human brain filters information (like recognizing patterns and identifying objects). From a science point of view, both ML and DL can be applied to various scientific domains to analyze large datasets, handle noise correction, deal with error classification, and classify features in data.

This training will introduce AI/ML/DL principles used for science in an HPC environment. After learning the “basics”, participants will then be able to apply techniques learned to run hands-on examples using OLCF’s Ascent system.

For more information or to register, see https://www.olcf.ornl.gov/calendar/ai-for-science-at-scale-intro/

General sign-ups are still open, but registration for the hands-on portion is now closed due to high demand. Hands-on examples will be available after the event for everyone.

AI Training Series: AI for Science at Scale – Introduction
June 15, 1:00 pm – 3:00 pm EDT

Machine learning (ML) is a subset of Artificial Intelligence (AI) that uses statistical learning algorithms to build applications that can automatically learn and improve from its experiences. Deep learning (DL) is a subset of ML that is inspired by the way a human brain filters information (like recognizing patterns and identifying objects). From a science point of view, both ML and DL can be applied to various scientific domains to analyze large datasets, handle noise correction, deal with error classification, and classify features in data.

This training will introduce AI/ML/DL principles used for science in an HPC environment. After learning the “basics”, participants will then be able to apply techniques learned to run hands-on examples using OLCF’s Ascent system.

For more information or to register, see https://www.olcf.ornl.gov/calendar/ai-for-science-at-scale-intro/

General sign-ups are still open, but registration for the hands-on portion is now closed due to high demand. Hands-on examples will be available after the event for everyone.

Upcoming Downtimes

  • Frontier will be unavailable from 8:00 AM until 8:00 PM on Tuesday, June 06
  • Marble will be upgraded from OpenShift v4.10.52 to v4.10.59 starting at 08:00 AM on June 13 through 08:00 AM on June 14. During this time, Marble cluster should remain available.  Jupyter notebooks are stateful and single instance workloads which will be deleted/recreated as part of the node upgrade process.

Center Announcements

OLCF Office Hours Sign-up is now available in myOLCF

Starting in June, users will now be able to sign-up for OLCF Office Hours via myOLCF. OLCF Office Hours are offered every Monday from 2-3 pm ET and Wednesday from 1-2 pm ET and provide direct access to OLCF and partner vendor staff to discuss current issues or questions about running applications on OLCF systems including Frontier. For more information and to sign-up please see: https://docs.olcf.ornl.gov/#olcf-office-hours

May 2023 OLCF User Conference Call – OLCF Storage
May 31, 12:00 pm-1:00 pm ET

The May OLCF User Conference Call will be held from noon until 1:00 PM Eastern Time on Wednesday, May 31. During this call, OLCF’s Suzanne Parete-Koon and Jesse Hanley will give an overview of the many areas that OLCF has for storage, how to move data between them, and give best practices for using the Orion Filesystem. For more information, see the event page at https://www.olcf.ornl.gov/calendar/userconcall-may2023/