NVIDIA A100 80GB GRAPHIC CARD
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NVIDIA A100 80GB
Unprecedented Acceleration for World’s Highest-Performing Elastic Data Centers
The NVIDIA A100 80GB Tensor Core GPU delivers unprecedented acceleration—at every scale—to power the world’s highest performing elastic data centers for AI, data analytics, and high-performance computing (HPC) applications. As the engine of the NVIDIA data center platform, A100 provides up to 20x higher performance over the prior NVIDIA Volta generation. A100 can efficiently scale up or be partitioned into seven isolated GPU instances, with Multi-Instance GPU (MIG) providing a unified platform that enables elastic data centers to dynamically adjust to shifting workload demands.
A100 is part of the complete NVIDIA data center solution that incorporates building blocks across hardware, networking, software, libraries, and optimized AI models and applications from NGC. Representing the most powerful end-to-end AI and HPC platform for data centers, it allows researchers to deliver real-world results and deploy solutions into production at scale, while allowing IT to optimize the utilization of every available A100 GPU.
Data Center Class Reliability
Designed for 24 x 7 data center operations and driven by power-efficient hardware and components selected for optimum performance, durability, and longevity. Every NVIDIA A100 board is designed, built and tested by NVIDIA to the most rigorous quality and performance standards, ensuring that leading OEMs and systems integrators can meet or exceed the most demanding real-world conditions.
Secure and measured boot with hardware root of trust technology within the GPU provides an additional layer of security for data centers. A100 meets the latest data center standards and is NEBS Level 3 compliant. The NVIDIA A100 includes a CEC 1712 security chip that enables secure and measured boot with hardware root of trust, ensuring that firmware has not been tampered with or corrupted.
NVIDIA Ampere Architecture
NVIDIA A100 is the world’s most powerful data center GPU for AI, data analytics, and high-performance computing (HPC) applications. Building upon the major SM enhancements from the Turing GPU, the NVIDIA Ampere architecture enhances tensor matrix operations and concurrent executions of FP32 and INT32 operations.
More Efficient CUDA Cores
The NVIDIA Ampere architecture’s CUDA cores bring up to 2.5x the single-precision floating point (FP32) throughput compared to the previous generation, providing significant performance improvements for any class or algorithm or application that can benefit from embarrassingly parallel acceleration techniques.
Third Generation Tensor Cores
Purpose-built for deep learning matrix arithmetic at the heart of neural network training and inferencing functions, the NVIDIA A100 includes enhanced Tensor Cores that accelerate more datatypes (TF32 and BF16) and includes a new Fine-Grained Structured Sparsity feature that delivers up to 2x throughput for tensor matrix operations compared to the previous generation.
PCIe Gen 4
The NVIDIA A100 supports PCI Express Gen 4, which provides double the bandwidth of PCIe Gen 3, improving data-transfer speeds from CPU memory for data-intensive tasks like AI and data science.
High Speed HBM2e Memory
With 80 gigabytes (GB) of high-bandwidth memory (HBM2e), the NVIDIA A100 PCIe delivers improved raw bandwidth of 1.55TB/sec, as well as higher dynamic random access memory (DRAM) utilization efficiency at 95 percent. A100 PCIe delivers 1.7x higher memory bandwidth over the previous generation.
Error Correction Without a Performance or Capacity Hit
HBM2e memory implements error correction without any performance (bandwidth) or capacity hit, unlike competing technologies like GDDR6 or GDDR6X.
Compute Preemption
Preemption at the instruction-level provides finer grain control over compute and tasks to prevent longer-running applications from either monopolizing system resources or timing out.
| Weight | 2 kg |
|---|---|
| brands | NVIDIA |
| Weight | 5 kg |
|---|---|
| Brand | Nvidia |
| Graphics Card | Nvidia |
| Architecture | Ampere |
| Process Size | 7nm | TSMC |
| Transistors | 54 Billion |
| Die Size | 826 mm2 |
| CUDA Cores | 6912 |
| Streaming Multiprocessors | 108 |
| Tensor Cores | Gen 3 | 432 |
| Multi-Instance GPU (MIG) Support | Yes, up to seven instances per GPU |
| FP64 | 9.7 TFLOPS |
| FP64 Tensor Core | 19.5 TFLOPS |
| FP32 | 19.5 TFLOPS |
| TF32 Tensor Core | 156 TFLOPS | 312 TFLOPS* |
| BFLOAT16 Tensor Core | 312 TFLOPS | 624 TFLOPS* |
| FP16 Tensor Core | 312 TFLOPS | 624 TFLOPS* |
| INT8 Tensor Core | 624 TOPS | 1248 TOPS* |
| INT4 Tensor Core | 1248 TOPS | 2496 TOPS* |
| NVLink | 2-Way Low Profile, 2-Slot |
| NVLink Interconnect | 600 GB/s Bidirectional |
| GPU Memory | 80GB HBM2e ECC on by Default |
| Memory Interface | 5120-bit |
| Memory Bandwidth | 1555 GB/s |
| System Interface | PCIe 4.0 x16 |
| Thermal Solution | Passive |
| vGPU Support | NVIDIA Virtual Compute Server with MIG support |
| Secure and Measured Boot Hardware Root of Trust | CEC 1712 |
| NEBS Ready | Level 3 |
| Power Connector | 8-pin CPU |
| Maximum Power Consumption | 300 W |
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