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Product Overview |
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The Dell NVIDIA Tesla A40 48GB Deep Learning GPU Graphics Card offers robust graphics processing designed for AI, machine learning, and data center workloads. It fits seamlessly into high-performance computing setups where handling large models and datasets is essential. |
General Information |
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| Brand | Dell |
| Part Number | 900-2G133-0100-130 |
Technical Information |
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| Chipset | Nvidia |
| Bus Interface | PCI Express 4.0 x16 |
| Supported APIs | DirectX 12, OpenGL: 4.6, OpenCL, OpenCL: 3.0, Vulkan: 1.2.175 , CUDA, Shader Model: 6.7, DirectCompute |
| Output Interface | No Display Outputs (Compute Card) |
Memory |
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| Memory Size | 48GB |
| Interface | GDDR6 |
| Memory Bus | 384-bit |
Physical Characteristics |
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| Slot Width | Dual-slot |
| 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 Dell NVIDIA Tesla A40 is a powerful GPU designed specifically for deep learning, AI, and high-performance computing applications. It offers substantial memory and processing capabilities, enabling researchers and data scientists to train complex models and handle large datasets efficiently. Often found in data centers and enterprise environments, this graphics card fits well in servers dedicated to machine learning, scientific simulations, and visualization tasks. It's built to accelerate workloads that require massive parallel processing and fast memory access. Key Features
This GPU is typically deployed in professional research labs and enterprise AI clusters where both speed and reliability are crucial. By providing a strong computational backbone, it helps users reduce training times and improve model accuracy in demanding environments. |
Use Cases |
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The Dell NVIDIA Tesla A40 48GB GPU is typically deployed in enterprise data centers and research institutions where large-scale AI and deep learning models demand high computational capacity. IT architects and data scientists benefit from its ability to handle extensive datasets and complex neural networks efficiently. How It's Used:
By integrating the Tesla A40 into high-throughput computing environments, organizations can improve operational efficiency through faster processing and better resource utilization. Its compatibility with existing data center infrastructures ensures scalability and sustained performance for evolving AI workloads. |