Review the complete academic findings detailing the memory-mapped virtual pipeline bypass architecture.
As distributed deep learning architectures and multi-agent pipelines scale, traditional inter-process communication (IPC) frameworks introduce unsustainable operating system overhead. Standard transport layers, such as gRPC and TCP/IP, impose a significant “Interconnect Tax” due to multi-stage serialization, kernel-space context switching, and redundant memory copies. We present the Neural-Native Interconnect (NNI), an open, lightweight hardware-aware protocol engineered to bypass traditional kernel routing. By utilizing memory-mapped shared registries, packed C-struct alignment, and hardware-enclave TEE integration, NNI achieves sub-microsecond intra-node latencies (0.0007 ms) with near-zero CPU overhead.