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| Product Overview |
|---|
The CX654106A Mellanox ConnectX-6 is a dual-port 100Gb/s QSFP56 socket direct adapter designed to fit into high-performance servers and storage devices. It provides fast, reliable network connectivity suited for data centers and computing environments that prioritize speed and low latency. |
| General Information | |
|---|---|
| Brand | Mellanox |
| Part Number | CX654106A |
| Technical Information | |
|---|---|
| Chipset/Controller | Mellanox ConnectX-6 |
| Virtualization Support | SR-IOV, VXLAN, NVGRE, Geneve, NetQueue, vNIC |
| Data Rate (Speed) | 100GbE |
| Data Center Bridging | Yes |
| Storage Over Ethernet | iSCSI, SMB Direct |
| Interface (Bus) | PCIe 4.0 x16 |
| Number of Ports | 2-Port (Dual) |
| OS Compatibility | Windows Server 2022, VMware ESXi 8.0, RHEL, VMware ESXi |
| Network Management | SNMP, RMON, NC-SI, IPMI |
| Offload Support | RDMA, RoCE v2, iSCSI, PXE Boot, Wake-on-LAN (WoL), RoCE v1, iWARP, TCP Stateless Offload, Jumbo Frames |
| Bracket Height | Full Height (Standard) |
| Connectivity & Physical | |
|---|---|
| Form Factor | Standard PCIe Card |
| Port Type | QSFP56 |
| Cabling Type | AOC |
| Max Power Consumption | Typical: 25W, Max: 35W |
| Weight | 3.00 |
| Condition | Refurbished |
| Miscellaneous | |
|---|---|
| Assembly Required | Yes |
| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, cURus, CE, FCC, UL, TUV |
| Product Description |
|---|
The CX654106A Mellanox ConnectX-6 adapter is built for high-performance networking, delivering dual 100Gb/s ports through QSFP56 connectors. It's commonly used in data centers and high-performance computing setups to ensure fast and reliable data flow. Often found in enterprise servers and storage systems, this adapter is favored by network engineers and IT professionals who require robust and scalable connectivity solutions. It supports advanced features like RDMA and congestion control to optimize network efficiency. Key Features
This adapter is typically deployed in modern data centers, cloud infrastructures, and HPC clusters where network performance is critical. It plays a key role in reducing bottlenecks and supporting large-scale data processing. |