NVIDIA

NVIDIA MCX755106AS-HEAT | 200GbE/NDR200 IB, 2x QSFP112, HHHL (tall bracket), PCIe 5.0 x16, Secure Boot

SKU:MCX755106AS-HEAT

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Description

HHHL adapter with tall bracket featuring dual QSFP112 ports for 2x200GbE or NDR200 InfiniBand. Provides PCIe Gen5 x16 throughput, Secure Boot, RDMA/RoCE, NVMe-oF offloads, and precise PTP hardware timestamping for AI/HPC and modern data center fabrics.

Features

- Dual 200G QSFP112 for high-density Ethernet or InfiniBand
- PCIe Gen5 x16 for maximum host connectivity
- Secure Boot and device security features
- RDMA and NVMe-oF acceleration
- SR-IOV and OVS/overlay offloads
- PTP 1588v2 hardware timestamping for precision timing

Warranty

All products sold by XS Network Tech include a 12-month warranty on both new and used items. Our in-house technical team thoroughly tests used hardware prior to sale to ensure enterprise-grade reliability.

All technical data should be verified on the manufacturer data sheets.

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FAQs

Technical Specifications

FAQs

Q: What bracket is included?
A: A tall/full-height bracket is indicated for this model.

Q: Can I switch between Ethernet and InfiniBand?
A: Yes, the adapter can operate as 200GbE or NDR200 InfiniBand.

Q: Does it support Secure Boot?
A: Yes, Secure Boot and device attestation features are supported.

Q: Are optics or cables included?
A: No, QSFP112 optics or cables must be purchased separately.

Q: Is RDMA supported over Ethernet?
A: Yes, via RoCE v2 for low-latency Ethernet networking.

Technical Specifications

- Controller: ConnectX-7
- Network modes: 2x 200GbE or NDR200 InfiniBand (selectable)
- Ports: 2x QSFP112 (each up to 200G)
- Form factor: HHHL with tall/full-height bracket
- Host interface: PCIe 5.0 x16
- Security: Secure Boot, device attestation
- Virtualization: SR-IOV, OVS offloads, VXLAN/GRE/Geneve
- RDMA: RoCE v2 and InfiniBand verbs
- Storage: NVMe-oF/RDMA acceleration
- Timing: IEEE 1588v2 PTP hardware timestamping
- Cabling/optics: QSFP112 200G optics, AOC, or DAC (not included)
- Operating systems: Major Linux distributions and hypervisors
- Use cases: AI/ML clusters, HPC, enterprise core networks

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