AI & Machine Learning

PRISM: Breaking the O(n) Memory Wall in Long-Context LLM Inference via O(1) Photonic Block Selection

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PRISM, a photonic accelerator, addresses the memory bottleneck in long-context large language model inference by using O(1) photonic block selection to fetch relevant KV blocks, significantly reducing memory bandwidth costs. This breakthrough is crucial for developers and tech professionals as it enables more efficient processing of long contexts without increasing computational resources, offering up to 16x traffic reduction and a four-order-of-magnitude energy advantage over GPUs at practical context lengths.

Read the full article at arXiv cs.AI (Artificial Intelligence)

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