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Product Overview |
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The Cisco NVIDIA Tesla T4 16GB GDDR6 PCIe 3.0 x16 GPU Accelerator Card is a versatile solution aimed at accelerating AI and high-performance computing workloads. It fits into servers and workstations that require efficient processing power for tasks like machine learning inference and data analysis, providing a balance between performance and energy usage. |
General Information |
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| Brand | Cisco |
| Part Number | 900-2G183-6200-000Z |
| Series | NVIDIA Tesla T4 |
Miscellaneous |
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| Compliance Standards | WEEE, RoHS, CE, FCC |
Physical Characteristics |
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| Weight | 3.00 |
| Condition | Refurbished |
Product Description |
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The NVIDIA Tesla T4 GPU accelerator card is built for accelerating machine learning, deep learning, and data analytics tasks. It's commonly found in data centers and server environments where high-performance computing is essential. Engineered for professionals working with AI models, scientists, and developers, this GPU provides a balance between power efficiency and computing performance. Key Features
This accelerator card is typically deployed in cloud computing, data analytics, and AI inference applications. Its efficient design helps organizations run demanding tasks without requiring excessive power or cooling resources. Users benefit from faster model training and inference speeds, enabling quicker insights and development cycles in research and enterprise environments. |
Use Cases |
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The Cisco NVIDIA Tesla T4 GPU Accelerator Card is typically deployed in data centers and enterprise server environments that demand efficient AI inference and machine learning processing. IT teams and data scientists leveraging virtualization or containerized workloads benefit from its balance of performance and power efficiency in compact hardware configurations. How It's Used:
This GPU accelerator card enables organizations to improve throughput and reduce latency for AI-driven applications, facilitating scalable and efficient computing across diverse server infrastructures. Its integration into existing data center hardware supports operational continuity while addressing the computational demands of evolving workloads. |