NVIDIA BlueField Data Processing Units (DPUs) are designed to offload, accelerate, and isolate infrastructure tasks that traditionally consume significant host CPU cycles. In modern AI storage architectures, tasks such as NVMe-over-Fabrics (NVMe-oF) target emulation, hardware-accelerated encryption, and data compression are extremely CPU-intensive. By integrating BlueField DPUs into the storage fabric, these 'Infrastructure' tasks are handled by the DPU's dedicated ARM cores and hardware acceleration engines. This reduces the load on the host CPU, freeing up those cores to focus entirely on application logic and feeding the GPUs. While DPUs do enhance I/O performance and reduce latency (Options B and D), those are indirect benefits of the fundamental architectural shift of offloading. The direct, primary benefit cited in NVIDIA's DOCA and BlueField documentation is the reclamation of host CPU resources, effectively turning a standard server into a more efficient 'AI-ready' node.