Stop Making GPUs Reprocess Every Token | So We Built It

Pure Key-Value Accelerator (KVA) keeps your models' KV cache in shared storage, so any GPU in the fleet can reuse it instead of recomputing it. Robert Alvarez, Principal Solutions Architect at Everpure, traces KVA back to a realization about a year and a half ago: storage needed to play a bigger role in AI inference. Picture two servers running the same model. A conversation is first processed on node one, and when the user comes back days later, node one is overloaded and node two has the room to serve it. Because node two has never seen that conversation, it has to reprocess every token of the history before it can respond. A transformer model computes keys and values for every token it reads and uses them to generate the next token. When KVA recognizes a conversation it has already seen, it loads those stored keys and values directly into the model's memory, so the response starts faster no matter which GPU is serving it. Learn more about Pure Key-Value Accelerator: https://support.everpuredata.com/r/pure-kva/pure-kva-overview-and-architecture The Architecture Behind More Efficient AI Inference: https://blog.everpuredata.com/perspectives/the-architecture-behind-more-efficient-ai-inference/