DWI: Efficient On-Device LLM Decoding Through Dynamic Width Selection on Nested Models
Deploying large language models (LLMs) on resource-constrained mobile devices remains a significant challenge due to memory limitations and high I/O overhead. While existing dynamic sparsity methods reduce computation costs, they often suffer from inefficient loading patterns that degrade I/O throughput. To address thi...