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Product Overview |
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The HP NVIDIA Tesla V100 PCIe 32GB GPU Module is designed to accelerate machine learning, data analytics, and scientific workloads within high-performance computing environments. It fits into PCIe expansion slots of servers like the Apollo 6500 Gen10, helping users run demanding computations more efficiently and reliably. |
General Information |
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| Brand | HPE |
| Part Number | P05913-001 |
| Series | NVIDIA Tesla V100 |
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 V100 PCIe 32GB GPU Module is built for demanding compute tasks like artificial intelligence, deep learning, and scientific simulations. You’ll often find this GPU in high-performance servers such as the Apollo 6500 Gen10, where it handles massive parallel processing efficiently. Engineered for data scientists, researchers, and enterprise IT teams, this module accelerates workloads that require intensive matrix calculations and large-scale data handling. It fits into standard PCIe slots, making it a versatile addition to various server setups. Key Features
This GPU module is commonly deployed in research labs, AI startups, and enterprise data centers where performance at scale is critical. It enables smoother handling of complex models and large data volumes without bottlenecking other system components. |
Use Cases |
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The HP NVIDIA Tesla V100 PCIe 32GB GPU Module is primarily deployed in enterprise data centers and high-performance computing clusters where complex AI and scientific computations demand substantial parallel processing power. Organizations running deep learning frameworks and large-scale simulation workloads benefit from its integration within server platforms such as the Apollo 6500 Gen10. How It's Used:
By leveraging the Tesla V100 GPU module, organizations improve computational throughput and scalability in demanding workloads. Its PCIe design allows for flexible integration into existing rack deployments, facilitating efficient resource allocation and workload acceleration across diverse server infrastructures. |