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| Product Overview |
|---|
The IBM NVIDIA Grid K1 16GB GDDR3 PCI-Express x16 Video Graphics Card is designed to provide virtualized graphics acceleration within data center servers. It fits into environments that require multiple users to access GPU resources simultaneously, such as virtual desktops or remote workstations, offering a balance between memory capacity and virtualization features without being overly specialized. |
| General Information | |
|---|---|
| Brand | IBM |
| Part Number | 90Y2431 |
| Alternate Part Number | 90Y2431-02-UK |
| Technical Information | |
|---|---|
| Chipset | Nvidia |
| Bus Interface | PCI-Express x16 |
| Memory | |
|---|---|
| Memory Size | 16GB |
| Interface | GDDR3 |
| Physical Characteristics | |
|---|---|
| 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 |
|---|
The IBM NVIDIA Grid K1 16GB GDDR3 PCI-Express x16 Video Graphics Card is built to handle demanding virtualized graphics environments. Often found in data centers and enterprise setups, this card supports multiple users accessing high-performance graphics remotely. Commonly used in virtual desktop infrastructure (VDI), it’s ideal for businesses deploying graphics-intensive applications like CAD, 3D modeling, or video editing across virtual machines. IT professionals and system administrators benefit from its ability to deliver consistent GPU resources to multiple users simultaneously. Key Features
This graphics card is typically deployed in virtualized server environments where multiple users need access to GPU acceleration without dedicated hardware. It plays a key role in enhancing productivity by delivering reliable graphics performance in shared setups. |
| Use Cases |
|---|
The 90Y2431 IBM NVIDIA Grid K1 is intended for use in environments requiring shared virtual graphics resources. How It's Used:
This card enables organizations to efficiently allocate GPU resources, improving performance and user experience across virtualized systems. |