GPU-Resident Top-K for Agentic RAG: I Built a CUDA Kernel So My Retrieval Step Would Stop Bouncing Off the GPU

A hidden "round-trip tax" silently kills the performance of agentic RAG pipelines, as each retrieval query bounces from the GPU to the CPU for processing and back again. A custom CUDA kernel eliminates this bottleneck by keeping the entire data corpus resident on the GPU, handling the complete similarity search and selection process on-device. This GPU-resident architecture dramatically reduces latency, achieving up to an 8.6x speedup compared to CPU-based methods