NVIDIA A100-40G GPU – 40GB SXM4 High-Performance Computing Accelerator (Converted)
NVIDIA A100-40G GPU – 40GB SXM4 High-Performance Computing Accelerator (Converted)

NVIDIA A100-40G GPU – 40GB SXM4 High-Performance Computing Accelerator (Converted)

Regular price $5,690.00
Sale price $5,690.00 Regular price $5,990.00
Unit price
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Jacket Size US Size UK Size Bust Waist Hips Sleeves
XXS 0 2 79 - 83 63 - 67 83 - 87 60
XS 0 - 2 4 - 6 84 - 88 68 - 72 88 - 92 61
S 4 - 6 8 - 10 89 - 93 73 - 77 93 - 97 62
M 8 - 10 12 - 14 94 - 98 78 - 82 98 - 105 63.5
L 12 - 14 16 - 18 99 - 103 83 - 87 103 - 107 64.5
XL 16 - 18 20 - 22 106 - 112 91 - 97 111 - 117 66
2XL 20 - 22 24 - 26 116 - 122 101 - 107 121 - 127 66
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Jacket Size US Size UK Size Chest Waist Hips Sleeves
XS 34 34 84 - 88 70 - 74 85 - 89 63
S 36 36 89 - 93 75 - 79 90 - 94 64
M 38 - 40 38 - 40 94 - 100 80 - 86 95 - 101 65
L 42 - 44 42 - 44 101 - 108 87 - 94 102 - 109 66
XL 46 - 48 46 - 48 109 - 116 95 - 102 110 - 116 67
2XL 50 - 52 50 - 52 117 - 124 103 - 110 117 - 123 68
3XL 54 - 56 54 - 56 125 - 132 111 - 118 124 - 130 69
Brand: Nvidia
MPN: A100-40G
Condition: Refurbished

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The NVIDIA A100-40G GPU is a high-performance computing accelerator with 40GB of HBM2 memory, originally designed for the SXM4 interface and now offered as a converted unit. This powerful GPU is engineered to accelerate AI, data analytics, and high-performance computing (HPC) workloads, delivering unprecedented speed and scalability for demanding tasks in modern data centers.

✅ Key Features: NVIDIA Ampere Architecture: Powers the latest advancements in AI and HPC. 40GB HBM2 Memory: Provides massive memory bandwidth for handling large datasets and complex models. Tensor Cores: Accelerates AI training, inference, and HPC simulations with dedicated processing capabilities. SXM4 Interface (Converted): Adapted for broad compatibility while retaining core performance benefits. High-Performance Computing: Ideal for scientific research, data analytics, and complex simulations. AI and Deep Learning Acceleration: Significantly speeds up training and deployment of neural networks.

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