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๐Ÿ“š An Efficient AI Approach to Memory Reduction and Throughput Enhancement in LLMs


๐Ÿ’ก Newskategorie: AI Nachrichten
๐Ÿ”— Quelle: marktechpost.com

The efficient deployment of large language models (LLMs) necessitates high throughput and low latency. However, LLMsโ€™ substantial memory consumption, particularly by the key-value (KV) cache, hinders achieving large batch sizes and high throughput. The KV cache, storing keys and values during generation, consumes over 30% of GPU memory. Various approaches such as compressing KV sequences [โ€ฆ]

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