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0VFJ45 Dell NVIDIA Tesla V100 16GB HBM2 Passive CUDA GPU Accelerator Card
SKU:
0VFJ45
Weight: 3.00 lbs
Condition: Refurbished
- 16GB HBM2 memory for high-bandwidth data processing
- Passive cooling design suitable for dense server environments
- Powered by NVIDIA Tesla V100 GPU with CUDA cores for accelerated computing
- Optimized for AI, machine learning, and scientific simulations
In stock
$1,037.96
Product Overview |
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The Dell NVIDIA Tesla V100 16GB GPU accelerator card is a high-performance computing device tailored for intensive workloads like AI and scientific simulations. It fits into server environments where passive cooling is preferred, offering powerful CUDA-enabled processing alongside large, fast memory to manage complex tasks efficiently. |
General Information |
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| Brand | Dell |
| Part Number | 0VFJ45 |
| Series | NVIDIA Tesla V100 16GB |
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 Dell NVIDIA Tesla V100 16GB GPU accelerator card is built to handle demanding computational tasks with ease. It commonly finds application in data centers, research labs, and enterprise servers where heavy GPU workloads are routine. Designed for professionals working on AI training, machine learning models, and large-scale simulations, this card delivers robust performance without the need for active cooling. Key Features
This GPU accelerator is frequently deployed in server rooms where airflow and space constraints favor passive cooling solutions. It plays a vital role in speeding up workflows that involve heavy numerical calculations, reducing the time needed for training AI models or running simulations. The combination of advanced GPU architecture and efficient design makes it a reliable choice for professionals demanding steady, high-performance compute power. |
Use Cases |
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The Dell NVIDIA Tesla V100 16GB GPU accelerator card is primarily deployed in high-density server racks within enterprise data centers and research institutions. It serves IT professionals and data scientists who require substantial computational power for large-scale AI model training, machine learning inference, and complex simulations under demanding thermal constraints. How It's Used:
This GPU accelerator card enables organizations to optimize compute density while maintaining thermal efficiency in passive-cooled environments. Its large memory and CUDA capabilities support scalable workloads, enhancing throughput and operational reliability in complex computational ecosystems. |
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