Nvidia says it can shrink LLM memory 20x without changing model weights

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.

New KV cache compaction technique cuts LLM memory 50x without accuracy loss

MIT researchers developed Attention Matching, a KV cache compaction technique that compresses LLM memory by 50x in seconds — ...
TMCnet

Penguin Solutions Introduces Industry's First Production-Ready CXL-Based KV Cache Server

Accelerating memory-dependent AI processes, Penguin's MemoryAI KV cache server increases memory capacity by integrating 3 TB of DDR5 main memory and up to eight 1 TB CXL Add-in Cards (AICs). Penguin ...
Electronic Design

Adding Cache to IPs and SoCs

Cache memory significantly reduces time and power consumption for memory access in systems-on-chip. Technologies like AMBA protocols facilitate cache coherence and efficient data management across CPU ...