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Galahad: GPUs Never Read Text Twice
19 Oct
Summary
- Galahad saves GPU's KV cache to encrypted NVMe.
- It avoids rereading text after GPU memory clears.
- No special hardware needed, only NVMe SSD.
Corbenic AI has launched the beta for Galahad, a system designed to prevent GPUs from rereading already processed text. This innovation saves a model's key-value (KV) cache, the attention state generated as a model reads a prompt, to encrypted local NVMe storage.
The stored cache is reloaded the next time identical text appears, significantly speeding up AI processing. Founder Sietse Schelpe emphasizes that Galahad requires no special hardware, relying on existing NVMe SSDs within a server to act as extended working memory for AI.
This approach addresses the costly repetition of prefill computations in standard AI serving. Galahad's Taliesin component writes text state to disk under a secure fingerprint and reloads it upon reappearance. The system operates on a fail-closed principle: serve without memory, never with incorrect memory.
Galahad's KV persistence offers an alternative to other solutions by focusing on exact, fail-closed reuse within a single library. The company highlights its security features, including encryption and customer data isolation, to protect sensitive AI working memory.
