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Challenge: Inconsistent Batch Time
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Classroom Contents
Refurbish Your Training Data - Reusing Partially Augmented Samples for Faster Deep Neural Network Training
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- 1 Intro
- 2 DNN Training Pipeline
- 3 Overhead of Data Augmentation
- 4 Existing Approach: Data Echoing
- 5 Our Approach: Data Refurbishing
- 6 Analysis on Sample Diversity
- 7 Standard Training
- 8 Challenge: Inconsistent Batch Time
- 9 PyTorch Dataloader
- 10 Revamper
- 11 Balanced Eviction
- 12 Cache-Aware Shuffle
- 13 Implementation
- 14 Evaluation: Environments
- 15 Evaluation: Baselines
- 16 Evaluation: Accuracy & Throughput
- 17 Conclusion
