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SUMMARY:AI Training Series - Introduction to the LRZ AI Systems
DTSTART:20261124T090000Z
DTEND:20261124T160000Z
DTSTAMP:20261030T093600Z
UID:indico-event-578@events.hpc-portal.eu
DESCRIPTION:Contents\nThe aim of this course is to give an overview of the
  LRZ AI Systems\, and provide participants with the knowledge and skills n
 ecessary to efficiently utilise them. The course consists of mini lectures
 \, demos and hands on sessions (breaks included).\nBy participating in thi
 s lecture\, you will be able to:\n\nUnderstand the resources that the LRZ 
 AI System provides\nHow to allocate resources on the LRZ AI System and pro
 vision them with the needed software stack\nHow to interactively work with
  the LRZ AI Systems via the terminal (also Jupyter Notebooks for single GP
 U workload)\n\nUpon completion\, you will be able to effectively use the L
 RZ AI Systems to run Deep Learning workflows.\nBlocks of content:\n\nOverv
 iew of LRZ AI Systems (1h)\n\nHardware overview\nAccess mode for the diffe
 rent resources \nExecution Mode (software stack\n\n\n\n\nFundamentals of 
 Deep Learning (1.5h)\n\nIntroduction to Neural Network\nTraining Neural Ne
 twork\nExercises: Training Convolutional Neural Networks on GPUs\nExercise
 s: Training Transformers on GPUs\n\n\n\n\nDistributed Deep Learning Traini
 ng Part I (1.5h)\n\nMotivation for Distributed Deep Learning Training\nOve
 rview of Techniques for Distributed Deep Learning Trainin\n\n\n\n\nDistrib
 uted Deep Learning Training Part II (1.5h)\n\nData Parallelism\nExercise: 
 Multi-GPU Data Parallelism\nExercise: Multi-Node Data Parallelism\n\n\n\nP
 rerequisites\n\nAI Training Series: Orientation Session (or comparable pre
 vious knowledge)\nAI Training Series: Introduction to Container Technology
  & Application to AI at LRZ (or comparable previous knowledge)\nGood under
 standing of Deep Learning and Classical Machine Learning (courses such as 
 Introduction to Deep Learning (I2DL) (IN2346) are provided by TUM - materi
 al also available for non-TUM students)\n\nHands-On\nDuring the course a l
 ive demo on how to access and operate the LRZ AI system will be showcased.
  Exercises will be conducted on the LRZ AI Systems. In addition\, the para
 llelisation of the training of a ML model will be also demonstrated. \nCo
 ntent Level\nThe content level of the course is broken down as:\n\n\n\n\n\
 nBeginner's content:\n\n\n100%\n\n\n\n\nIntermediate content:\n\n\n0%\n\n\
 n\n\nAdvanced content:\n\n\n0%\n\n\n\n\nCommunity-targeted content:\n\n\n0
 %\n\n\n\n\n\nLanguage\nEnglish\nLecturers\nBenjamin Geißler and Dr. Mares
  Barekzai (both LRZ)\nPrices and Eligibility\nThe course is open and free 
 of charge for people from academia and industry affiliated with an institu
 tion in the Member States of the European Union or Associated/Other Countr
 ies to the Horizon 2020 programme.\nRegistration\nPlease apply with your o
 fficial email address to prove your affiliation. The final participants wi
 ll be selected and informed after the registration deadline has passed. Pr
 iority will be given to users of the LRZ AI systems\, who are kindly reque
 sted to provide their Project ID associated with the LRZ AI Systems in the
  registration form.\n \n\nhttps://events.hpc-portal.eu/event/578/
LOCATION:Online
URL:https://events.hpc-portal.eu/event/578/
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