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Vortex: Bridging Extreme Compression and Efficient LLM Inference

Shan, Haoxuan et al.
arXiv (All) · Papers
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Extreme compression techniques, including vector quantization (VQ) and input-dependent sparsity, can significantly reduce the memory footprint of large language models (LLMs). However, a key challenge remains in translating such compression into practical efficiency. On conventional systolic-array-b
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