Industry's first RDMA Ethernet based AI Memory Fabric System
Offloads GPU, HBM, and local head node DDR resource consumption
Drives down the cost of LLM inference at fleet scale
Enables seamless integration with LLM inference application frameworks
Under the Hood
Under the Hood
Powered by Enfabrica's 3.2 Tbps ACF SuperNIC silicon
Elastically connects up to 144 CXL memory lanes per system to resilient bundles of 400G / 800G RDMA Ethernet ports
Pooled memory target up to 18 TB CXL DDR5 DRAM per system (expandable to 28 TB in the future)
High memory bandwidth aggregation enabled by striping transactions across 18+ memory channels per system
Read access times in microseconds
Designed to interoperate with multiple GPU servers and initiator RDMA NICs
Delivers up to 50% lower cost per token per user
Delivers up to 50% lower cost per token per user
Ideal for agentic, batched, expert-parallel, high-turn, and/or large-context inference workloads
Equally deployable for AI training: activation storage offload, distributed checkpointing, optimizer state sharding
Software-enabled, high-performance caching hierarchy hides transfer latency within compute pipelines
Outperforms flash-based inference storage offload solutions with 100x lower latency and unlimited write/erase transactions
100% fabric-attached, headless memory free from head node CPU thread contention or locality constraints
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ACF-S: World’s highest throughput AI SuperNIC
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