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Product Overview |
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The HP NVIDIA Tesla M10 32GB GDDR5 Quad GPU Video Graphics Card combines four GPUs to support graphics virtualization in enterprise and data center environments. It delivers stable, multi-user performance tailored for virtualized applications and professional workloads. |
General Information |
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| Brand | HPE |
| Part Number | Q0J62A |
Technical Information |
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| Chipset | Nvidia |
| Bus Interface | PCI Express 3.0 x16 |
| Supported APIs | DirectX 11, DirectX 12, OpenGL: 4.5, OpenCL, CUDA, Shader Model: 5.1, DirectCompute |
| Output Interface | None (compute accelerator — no display outputs) |
Memory |
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| Memory Size | 32GB |
| Interface | GDDR5 |
Physical Characteristics |
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| Slot Width | Single-slot, low-profile (server form factor) |
| Weight | 3.00 |
| Condition | Refurbished |
Miscellaneous |
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| Assembly Required | Yes |
| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, cURus, CE, FCC, CCC, UL, TUV, cULus, CSA, cUL |
Product Description |
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The HP NVIDIA Tesla M10 is a powerful graphics card built to handle demanding virtual desktop infrastructure (VDI) and GPU-accelerated applications. It features four Tesla M10 GPUs working in parallel to provide efficient processing for multiple users simultaneously. Often found in data centers and enterprise environments, this card is designed for virtualization setups where numerous users require reliable and smooth graphical performance. IT professionals and organizations that rely on GPU virtualization benefit from its robust capabilities. Key Features
Commonly deployed in virtual desktop environments, the HP NVIDIA Tesla M10 helps ensure that users experience responsive graphics and computing power. It plays a critical role in facilitating GPU sharing and accelerating workloads in professional settings without sacrificing performance. |
Use Cases |
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The HPE NVIDIA Tesla M10 32GB GDDR5 Quad GPU Graphics Card is typically deployed in virtualized data center environments where multiple users require concurrent access to high-performance GPU resources. It suits enterprise IT infrastructures aiming to optimize graphics-intensive workloads across distributed teams and applications. How It's Used:
This graphics card enhances operational efficiency by consolidating multiple GPU resources into a single platform, enabling scalable and stable multi-user performance. Its design facilitates streamlined deployment and management in complex virtualization environments, ensuring consistent throughput for demanding GPU workloads. |