NVIDIA PRO A100 Tensor Core

Description

Designed for AI, HPC, and data analytics workloads:

* NVIDIA A100 GPU (Ampere Architecture) – Key Specifications
*  Category                   *  Specification                                   *
*——————–      *—————————————————*
*  GPU Architecture   * Ampere (GA100)                                     *
*  Process Node           * TSMC 7nm                                               *
*  FP32 Cores               * 6,912 CUDA Cores                                 *
*  Tensor Cores            * 432 (3rd Gen)                                         *
*  RT Cores                   * None (Not designed for ray tracing)  *
*  FP64 Performance  * 19.5 TFLOPS                                          *
*  FP32 Performance  * 19.5 TFLOPS                                          *
*  TF32 Performance  * 156 TFLOPS (with Tensor Core acceleration)        *
*  INT8 Performance  * 624 TOPS (with Sparsity)                   *
*  Memory (VRAM)    * 40GB or 80GB (HBM2e)                     *
*  Memory Bandwidth * 1,555 GB/s (40GB) / 2,039 GB/s (80GB)            *
*  NVLink Bandwidth * 600 GB/s (3rd Gen NVLink)             *
*  PCIe Support            * PCIe 4.0 x16                                          *
*  TDP (Power)             * 250W (40GB) / 400W (80GB)         *
*  Form Factors            * SXM4 (for servers) / PCIe (for workstations)      *
*  Multi-GPU Scaling  * NVLink & NVSwitch for multi-GPU systems (e.g., DGX A100) *
*  Key Features             * –  MIG (Multi-Instance GPU)  – Splits GPU into 7 isolated instances <br> –  Sparsity Acceleration  – 2x speed for sparse AI models <br> –  3rd Gen NVLink  – Scalable to multi-GPU systems *

* Use Cases :
✔  AI Training/Inference  (GPT-3, recommender systems)
✔  High-Performance Computing (HPC)  (scientific simulations)
✔  Data Analytics  (big data processing)
✔  Cloud Acceleration  (AWS, Azure, Google Cloud instances)

* Performance Highlights
–  5x faster  than previous-gen V100 in AI workloads (TF32/FP16).
–  Supports MIG  for cloud GPU partitioning (e.g., 7x 5GB GPU instances).
–  PCIe 4.0 & NVLink  for high-speed multi-GPU scalability.