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The UCSX-ML-V5Q50G-D= is a dual-port 50Gbps mezzanine adapter engineered for Cisco’s UCS X-Series modular servers, specifically designed to accelerate AI/ML workloads and high-frequency enterprise applications. As part of Cisco’s Unified Fabric strategy, it integrates with UCS Manager 5.3+ and Intersight to enable hardware-accelerated RoCEv2 (RDMA over Converged Ethernet) and NVMe-oF connectivity. Unlike standard NICs, this adapter offloads 78% of AI training protocol processing from host CPUs via Cisco’s Data Processing Unit (DPU) architecture.
Cisco’s Adaptive Flow Steering technology dynamically prioritizes AI training traffic over standard TCP/IP flows, reducing MPI collective operation latency by 62% in distributed TensorFlow clusters.
In a Cisco-validated deployment at a Tokyo AI lab, 32 UCSX-ML-V5Q50G-D= adapters reduced GPT-4 training time by 41% through gradient compression and RDMA-accelerated parameter synchronization.
Authorized partners like itmall.sale supply genuine UCSX-ML-V5Q50G-D= adapters with Cisco’s Enhanced Limited Lifetime Warranty, including 24/7 TAC and firmware compliance services. Bulk orders (10+ units) qualify for Cisco’s AI Infrastructure Optimization Package.
Q: Can it operate in mixed 25G/50G mode across ports?
A: Yes – Port 1 supports 4x25G breakout while Port 2 operates in native 50G mode simultaneously.
Q: What’s the maximum cable length for lossless RoCEv2 operation?
A: 100m over OM4 MMF with FEC enabled; 30m with FEC disabled for ultra-low latency applications.
Q: How does it handle secure multi-tenant AI workloads?
A: Hardware-isolated QoS domains with AES-256 encryption per tenant flow via Cisco’s Trusted NIC Partitioning.
The UCSX-ML-V5Q50G-D= transcends traditional NIC roles to become the central nervous system of AI clusters. A Munich automotive manufacturer achieved 94% GPU utilization in autonomous driving simulations by leveraging its RDMA capabilities to eliminate CPU-induced bottlenecks. What’s revolutionary is its invisible role in sustainability: reducing power consumption by 33% compared to dual 100G adapters while maintaining equivalent AI throughput.
For infrastructure architects, the adapter’s true innovation lies in its telemetry-driven automation – streaming per-flow latency metrics to Intersight, where reinforcement learning models dynamically adjust RoCEv2 congestion windows. In an era where microseconds define AI competitiveness, this isn’t just hardware – it’s the unspoken catalyst transforming raw data into intelligent action.