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FollowOLCF AI Training Series: AI for Science at Scale – Introduction, June 15, 2023
Introduction
This session is part of the OLCF’s AI for Science at Scale training series, and is open to NERSC users.
Overview
This training will provide an introduction to AI/ML/DL principles used for science in an HPC environment.
Machine learning (ML) is a subset of Artificial Intelligence (AI) that uses statistical learning algorithms to build applications that have the ability to automatically learn and improve from its experiences. Most of us use ML in our day to day life when we use services like search engines, voice assistants, and recommendations on Netflix. In ML, an algorithm is trained by providing it with a significant amount of data and allowing it to learn more about the processed information.
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). Since DL processes information in a similar manner as a human brain does, it is mostly used in applications that people generally perform (e.g., driverless cars being able to recognize a stop sign or distinguish a pedestrian from another object).
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.
As ML/DL models evolve to keep up with the complexity of the real world, a supercomputer’s resources get more and more valuable. In high-performance computing (HPC), ML/DL is getting more and more popular because of the sheer amount of data that needs to be processed and the computational power it requires.
After learning the “basics”, participants will then be able to apply techniques learned to run hands-on examples using OLCF’s Ascent system (equivalent to 1 cabinet of the Summit system). Although examples will be provided during the presentation, hands-on participation during the event is not required, and it is highly recommended to try the hands-on examples after the event so that you do not miss anything.
Date and Time: 10 am - 12 pm Pacific, Thursday, June 15, 2023
The format of this event will be online only. Registration
Registration is required for remote participation. Please find more information and register at the OLCF event page.
