O-2A: Outlier-Aware Compression for 8-bit Post-Training Quantization Model
Post Training Quantization (PTQ) is a practical and cost-effective technique that reduces main memory footprint of Deep Neural Networks (DNNs). However, the effectiveness of PTQ is limited by a notable decrease in accuracy when the precision falls below 8 bits. To overcome this limitation of PTQ, we...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10237192/ |