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| Product Overview |
|---|
The NVIDIA A100 80GB HBM2 PCI-E GPU Tensor Ampere Computing Accelerator Card combines large memory capacity with NVIDIA's Ampere architecture, delivering powerful tensor core acceleration and efficient multi-instance GPU capabilities for diverse computational tasks. |
| General Information | |
|---|---|
| Brand | Nvidia |
| Part Number | 699-21001-0230-610 |
| Technical Information | |
|---|---|
| Chipset | Nvidia |
| GPU Architecture | Ampere (NVIDIA) |
| Interface / PCIe Slot | PCIe 4.0 x16 |
| Supported Frameworks | CUDA, TensorRT, PyTorch, TensorFlow, JAX, MXNet, ONNX Runtime |
| Supported Precisions | FP64, FP32, TF32, BF16, FP16, INT8 |
| ECC Memory | Yes — Full ECC |
| Cooling Type | Passive |
| Memory | |
|---|---|
| Memory Size | 80GB |
| Interface | HBM2 |
| Memory Bus | 5120-bit |
| Miscellaneous | |
|---|---|
| Assembly Required | No |
| Compliance Standards | WEEE, RoHS, CE, FCC, TUV |
| Physical Characteristics | |
|---|---|
| Form Factor | Full-Height Full-Length (FHFL) |
| Weight | 3.00 |
| Condition | Refurbished |
| Product Description |
|---|
The NVIDIA A100 80GB HBM2 PCI-E GPU Tensor Ampere Computing Accelerator Card is engineered to deliver high performance for artificial intelligence, machine learning, and high-performance computing (HPC) tasks. It is commonly integrated into data center servers and workstations that require massive computational power. This accelerator card benefits researchers, data scientists, and enterprise IT professionals who need to accelerate complex computing workloads such as deep learning training and inference, scientific simulations, and data analytics. Key Features
With its substantial memory capacity and advanced architecture, the NVIDIA A100 80GB PCI-E GPU accelerator card enables efficient processing of the most demanding workloads. Its design ensures scalability and flexibility, making it a key component in modern AI and HPC infrastructure. |
| Use Cases |
|---|
The NVIDIA A100 80GB GPU accelerator card is widely utilized across various industries requiring advanced computational power. How It's Used:
Its versatility and performance make it suitable for organizations aiming to enhance their AI and HPC capabilities efficiently. |