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Product Overview |
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The HPE NVIDIA Tesla A10 24GB GPU Passive Cooler computing accelerator card is designed to enhance processing capabilities for AI, machine learning, and data analytics applications. It fits into server environments where efficient, quiet GPU acceleration is needed to handle complex computational tasks. |
General Information |
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| Brand | HPE |
| Part Number | 900-2G133-0320-030 |
| Series | NVIDIA Tesla A10 |
Miscellaneous |
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| Compliance Standards | WEEE, RoHS |
Physical Characteristics |
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| Weight | 3.00 |
| Condition | Refurbished |
Product Description |
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The HPE NVIDIA Tesla A10 computing accelerator card is built for intensive GPU-driven tasks such as artificial intelligence, machine learning, and high-performance computing. It features a large 24GB GDDR6 memory to handle demanding data sets and complex models efficiently. Often found in data centers and enterprise servers, this passive cooler variant minimizes noise and power usage, making it suitable for environments where airflow and acoustics are considerations. IT professionals and data scientists benefit from its reliable performance in accelerating computational workloads. Key Features
This accelerator card is typically deployed in server racks powering AI inference and training or scientific simulations. Its passive cooling makes it a good fit where airflow is managed carefully, helping maintain system stability without adding noise. |
Use Cases |
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The HPE NVIDIA Tesla A10 24GB GPU Passive Cooler accelerator card is ideal for deployment in data centers and enterprise server environments where quiet operation and efficient GPU processing are required. It serves organizations needing robust AI inference, machine learning, and HPC capabilities without introducing additional cooling noise or thermal management complexities. How It's Used:
This accelerator card supports operational efficiency by minimizing heat output and power consumption, enabling scalable GPU deployment in dense server racks. It enhances performance in computation-intensive workloads while maintaining a low acoustic footprint, which is critical for modern enterprise IT and research facilities. |