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Distributed Training Results
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Classroom Contents
Democratizing Machine Learning on Kubernetes
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- 1 Introduction
- 2 Who are we
- 3 Why is this important
- 4 Data Parallelization
- 5 Model Parallelization
- 6 Distributed Flow Training
- 7 Tensorflow Tools
- 8 Demos
- 9 Training Environment
- 10 Model Performance
- 11 Distributed Training
- 12 Distributed Training Results
- 13 Compute to Communication Ratio
- 14 Other Observations
- 15 How Can We Improve
- 16 Ubers
- 17 Cluster Performance
- 18 FreeFlow on CNI
- 19 GPU Resource Scheduler
- 20 Fast AI
