Training Objectives
Short introduction of the Karolina supercomputer How to access the Karolina GPU nodes First login Computing environment and available software libraries and tools HPC resources allocation, PBS Scratch and Project storages Special tools (Nodes availability overview, ...) Introduction to Data Parallel Deep Learning with Horovod Multi-node/-GPU aware Data Processing Pipelines Demonstration of Multi-node/-GPU Examples using Tensorflow Multi-node/-GPU Machine Learning with scikit-learn Efficient execution of a large number of small tasks transparently over HPC schedulers (SLURM/PBS) using HyperQueueTraining Contents
Access to Karolina's GPU accelerated part Efficient multi-GPU and multi-node execution of Deep and Machine Learning frameworks Introduction to HyperQueueDigital Innovation Hubs
IT4Innovations National Supercomputing CenterTechnology
- Artificial Intelligence
Technique
- Lecture
Channel
- Online
Technology Absortion Cycle
- Awareness of technology
Target Group
- Engineers
Instruction Level
- Intermediate
Sector
- Research & Development
Education Level
- Others:
Capacity
- More than 20
Details
Date: Completed - No longer available
Durations: 1h to 4h
Price: Free
Project
OtherCountries where training is provided
Czech RepublicCities where training is provided
OstravaLanguages this training can be provided
English
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