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Why We Need Quantization?
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Classroom Contents
Octo - INT8 Training with Loss-aware Compensation and Backward Quantization for Tiny On-device Learning
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- 1 Intro
- 2 Rise of On-device Learning
- 3 Common Compression Methods
- 4 The Workflow of DNN Training
- 5 Bridge the Gap: Data Quantization
- 6 Why We Need Quantization?
- 7 Potential Gains
- 8 Co-design of Network and Training Engine
- 9 Our System: Octo
- 10 Loss-aware Compensation
- 11 Backward Quantization
- 12 Evaluation Setup
- 13 Convergence Results
- 14 Ablation Study: Impact of LAC and PRC
- 15 Image Processing Throughput
- 16 Deep Insight of Feature Distribution Visualization of intermediate Feature Distribution
- 17 System Overhead
- 18 Conclusion
