Interní optická síťová karta Intel E810-XXVDA4 PCI Express

The Intel E810-XXVDA4 is an internal fiber network adapter with a PCI Express host interface, designed for high-speed wired connectivity in data centers and enterprise environments. It supports advanced offload and virtualization features to reduce latency and improve I/O efficiency for demanding network workloads.

Advantages

The adapter implements iWARP/RDMA for low-latency fabric services through kernel bypass, direct data placement, and transport acceleration. Intel Data Direct I/O (DDIO) enables direct transfers between the adapter and processor cache to lower latency, increase I/O bandwidth, and reduce power use. The card is PCI-SIG SR-IOV capable and supports Flexible Port Partitioning (FPP) to create multiple virtual functions from a single physical port, while Virtual Machine Device Queues (VMDq) offload VMM switching to hardware to reduce overhead and improve throughput.

Suitable for

• High-performance data center networking
• Enterprise servers requiring low-latency connectivity
• Virtualized environments with multiple VMs
• Applications using RDMA/iWARP for fast data transfer

Key specifications

• Model: Intel E810-XXVDA4
• Brand: Intel
• MPN: E810XXVDA4OCPV3
• EAN: 5032037225786
• Connectivity technology: Wired
• Interface: Fiber
• Host interface: PCI Express
• Supports iWARP/RDMA, Intel DDIO, SR-IOV, FPP, VMDq

How to use

Install the card into an available PCI Express slot on a compatible server motherboard and secure it according to the server manufacturer’s instructions. Connect the fiber link to the adapter’s fiber interface using appropriate transceivers and fiber cabling. Install vendor-provided drivers and firmware updates, then configure network settings and virtualization features (SR-IOV/FPP/VMDq) in the host operating system or hypervisor management console as required by your deployment.

Recommendations

Use certified fiber transceivers and maintain up-to-date drivers and firmware. Configure Intel DDIO and SR-IOV/FPP features in accordance with server and hypervisor best practices to achieve optimal latency, throughput, and resource partitioning.