arxiv preprint - Layer-Condensed KV Cache for Efficient Inference of Large Language Models

In this episode, we discuss Layer-Condensed KV Cache for Efficient Inference of Large Language Models by Haoyi Wu, Kewei Tu. The paper addresses the significant memory consumption issue in deploying large language models by proposing a novel method that computes and caches key-value pairs for only a small number of layers, thereby saving memory and enhancing inference throughput. Experiments demonstrate that this approach achieves up to 26× higher throughput compared to standard transformers while maintaining competitive performance. Additionally, the method can be integrated with existing memory-saving techniques for further efficiency improvements.