2023-11-07 AI Training Series - Introduction to the LRZ AI Systems (hdta3w23)
Course | AI Training Series - Introduction to the LRZ AI Systems |
Number | hdta3w23 |
Available places | 77 |
Date | 07.11.2023 – 07.11.2023 |
Price | EUR 0.00 |
Location | HYBRID: ONLINE/LRZ Boltzmannstr. 1 85748 Garching near Munich |
Room | Kursraum 2 |
Registration deadline | 02.11.2023 16:31 |
education@lrz.de |
Contents
The aim of this course is to give an overview of the LRZ AI Systems, and provide participants with the knowledge and skills necessary to efficiently utilise them. The course consists of mini lectures, demos and hands on sessions (breaks included) covering the following topics:
Resources overview of the LRZ AI Systems
Fundamentals of Deep Learning
Distributed Training of Neural Networks
Three blocks of content, devoting roughly an hour each to the first two, and two and a half hours to the third one:
- Overview of LRZ AI Systems (1h)
- Hardware overview (B)
- Access mode for the different resources (B)
- Execution Mode (software stack) (B) + (I)
15min Break
- Fundamentals of Deep Learning (1h)
Introduction to Neural Networks (B)
Training Neural Networks (B)
Introduction to Convolutional Neural Networks (B)
- Introduction to Transformers (B)
- Exercises: Training Convolutional Neural Networks and Transformers on GPUs (I)
1h Break
- Distributed Deep Learning Training Part I (1h)
- Motivation for Distributed Deep Learning Training (B)
- Overview of Techniques for Distributed Deep Learning Training (B)
15min Break
- Distributed Deep Learning Training Part II (1.5h)
- Data Parallelism (I)
- Exercise: Data Parallelism (I)
- Model Parallelism - Pipeline Parallelism and Tensor Parallelism (A)
- Demo: Pipeline Parallelism (A)
Prerequisites
- AI Training Series: Orientation Session (or comparable previous knowledge)
AI Training Series: Introduction to Container Technology & Application to AI at LRZ (or comparable previous knowledge)
Hands-On
During the course a live demo on how to access and operate the LRZ AI system will be showcased. In addition, the parallelisation of the training of a ML model will be also demonstrated.
Content Level
The content level of the course is broken down as:
Beginner's content: | 2:30h | 56% |
Intermediate content: | 1:30h | 33% |
Advanced content: | 0:30h | 11% |
Community-targeted content: | 0:00h | 0% |
Language
English
Lecturers
Navdar Karabulut, Ajay Navilarekal, Maja Piskac, Darshan Thummar (all LRZ)
Prices and Eligibility
The course is open and free of charge for people from academia and industry.
Registration
Please register with your official e-mail address to prove your affiliation. Following your successful registration, you will receive an invoice approx. 2 weeks before the course. After paying the invoice, you will not receive a receipt. If you require proof of payment (e.g., for reimbursement) please use a copy of the invoice together with your bank statement indicating the payment.
Withdrawal Policy
See Withdrawal
Legal Notices
For registration for LRZ courses and workshops we use the service edoobox from Etzensperger Informatik AG (www.edoobox.com). Etzensperger Informatik AG acts as processor and we have concluded a Data Processing Agreement with them.
See Legal Notices
No. | Date | Time | Leader | Location | Room | Description |
---|---|---|---|---|---|---|
1 | 07.11.2023 | 10:00 – 16:00 | Johannes Albert-von der Gönna Maja Piskac LRZ Events Darshan Thummar Ajay Navilarekal Navdar Karabulut | HYBRID: ONLINE/LRZ | Kursraum 2 | Lecture |