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Product Overview |
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The HP NVIDIA Tesla M10 32GB GDDR5 GPU Video Graphics Card delivers virtualization-focused GPU performance optimized for data centers and enterprise environments. It fits into setups requiring multiple simultaneous GPU instances to run virtual machines or GPU-accelerated applications, helping administrators provide reliable and scalable graphical processing power without dedicating separate GPUs for each user. |
General Information |
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| Brand | HPE |
| Part Number | 868798-001 |
Technical Information |
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| Chipset | Nvidia |
Memory |
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| Memory Size | 32GB |
| Interface | GDDR5 |
Miscellaneous |
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| Assembly Required | Yes |
| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, cURus, CE, FCC, CCC, UL, TUV, cULus, CSA, cUL |
Physical Characteristics |
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| Weight | 3.00 |
| Condition | Refurbished |
Product Description |
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The HP NVIDIA Tesla M10 32GB GDDR5 GPU Video Graphics Card is built for intensive virtualization workloads and GPU-accelerated tasks. It’s often found in data centers where multiple users require simultaneous access to powerful graphics processing, such as in virtual desktop infrastructure (VDI) setups. Commonly used by IT professionals and system administrators, this GPU enables efficient resource sharing without sacrificing performance. Its design supports environments where virtual machines need dedicated graphics acceleration, providing smooth and responsive user experiences. Key Features
This graphics card is typically deployed in enterprise data centers to bolster virtualized systems and GPU compute clusters. It plays a key role in improving efficiency by consolidating multiple GPU workloads into one card, reducing hardware overhead and operational complexity. |
Use Cases |
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The HPE NVIDIA Tesla M10 32GB GDDR5 GPU is primarily deployed in virtualization environments within data centers where multiple users require concurrent access to GPU resources. It is well-suited for enterprise IT operations that demand efficient GPU sharing across virtual machines without compromising performance. How It's Used:
This GPU card enhances operational efficiency by consolidating GPU resources, reducing hardware redundancy, and simplifying management in multi-tenant virtualization setups. Its ability to support multiple simultaneous GPU instances allows organizations to scale graphical processing capabilities dynamically as user demands evolve. |