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| Product Overview |
|---|
The Lenovo SR670 V2 PCIe x16/x16 Gen4 Riser Card extends the server's expansion capabilities by providing additional PCIe Gen4 slots in a compact form. It fits within the SR670 V2 chassis and supports high-speed devices, helping maintain efficient workflows in data-intensive environments. |
| General Information | |
|---|---|
| Brand | Lenovo |
| Part Number | 02JK733 |
| Alternate Part Number | 02JK733-13-CT |
| Technical Specification | |
|---|---|
| Host Interface | PCIe 4.0 (Gen4) x16 |
| Ports | 2 |
| Compatibility | Lenovo ThinkSystem SR670 V2, Lenovo SR670 V2 |
| Physical Characteristics | |
|---|---|
| Form Factor | PCIe x16/x16 Riser Card |
| Weight | 3.00 |
| Condition | Refurbished |
| Miscellaneous | |
|---|---|
| Assembly Required | Yes |
| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, cURus, CE, FCC, CCC, UL, TUV, cULus, CSA, cUL |
| Product Description |
|---|
This PCIe Gen4 riser card is built for Lenovo SR670 V2 servers, allowing users to expand the number of PCIe slots while maximizing data transfer speeds. Often found in data centers and enterprise environments, it suits workloads requiring fast connectivity for GPUs, NVMe drives, or network cards. Engineered to fit the SR670 V2 chassis, the riser card provides support for demanding applications like AI, HPC, and large-scale virtualization. IT professionals and system builders rely on this component to optimize server capacity without compromising performance. Key Features
Typically deployed in enterprise servers handling intensive compute or storage tasks, this riser card facilitates system customization and upgrade paths. It plays a key role in keeping servers adaptable and ready for evolving hardware needs. |
| Use Cases |
|---|
This riser card is typically used to enhance the expansion capabilities of Lenovo SR670 V2 servers by providing additional PCIe slots for high-performance components. How It's Used:
By enabling these expansions, the 02JK733 riser card helps optimize server performance and adapt to evolving computational demands. |