A coherent, intelligent, packet-switched memory fabric enables predictive, cache-coherent access across distributed compute, accelerator, and memory resources using a Memory-Fabric Transaction Layer Protocol (MF-TLP). MF-TLP defines routable packet formats for read, write, vectorized, atomic, reduction, collective, and predictive-prefetch transactions executed by memory-centric
network interface controllers (MC-NICs). Each MC-NIC performs packet
parsing, address translation, coherence management, and near-memory arithmetic or
tensor operations while coordinating with MF-TLP-aware switches providing hierarchical
directory control, multi-path routing, and in-network aggregation. Vectorized and multimodal packets
encode multiple addresses or
tensor offsets to reduce scatter / gather overhead, and programmable caching and quality-of-service modules manage tiered memory and tenant fairness. MF-TLP supports extension headers for predictive prefetch, collective coordination, and tenant governance, operating across hierarchical leaf-spine topologies using Ultra-
Ethernet Transport,
InfiniBand, or CXL fabrics. The
system delivers scalable, low-latency, memory-centric
orchestration for large-language-model training, multimodal AI, and data-intensive analytics.