Papers by Chungman Lee
A Frustratingly Easy Post-Training Quantization Scheme for LLMs (2023.emnlp-main)
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| Challenge: | Efficient inference is crucial for hyper-scale AI models, including large language models, as their parameter count continues to increase for enhanced performance. |
| Approach: | They propose a quantization scheme that fully utilizes the Transformer structure used in large language models to minimize the frequency of DRAM access while exploiting the parallelism of operations. |
| Outcome: | The proposed method minimizes the frequency of DRAM access while exploiting the parallelism of operations through a dense matrix format. |