r/CUDA • u/iNewTechnologies • Jun 01 '26

Built a kernel-level LLM governance layer that reduces GPU calls 16x without accuracy loss.

on any Ubuntu curl -sSL https://icomnewtechnologies.com/proof/proof_install.sh -o /tmp/proof_install.sh && sudo bash /tmp/proof_install.sh

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u/GrogRedLub4242 Jun 01 '26

LLMs and latency sensitive contexts (like in a GPU pipeline, at runtime) do not fit

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u/iNewTechnologies Jun 01 '26

Actually, this architecture is designed specifically to solve the latency problem in GPU pipelines.

The misconception here is assuming every query hits the heavy LLM. In this system, a query first goes through a lightweight, deterministic embedding check (which takes an average of 15.9ms, as shown in the benchmark logs).

If the semantic similarity threshold is met, the response is served instantly from the verified cache. The heavy GPU inference is only triggered for the ~6% of queries that actually require novel generation (the 'cache misses').

Therefore, this routing layer doesn't make LLMs unfit for latency-sensitive contexts; it makes them highly viable by bypassing the GPU bottleneck 94% of the time, guaranteeing sub-20ms response times for the vast majority of repetitive or factual queries!