NVIDIA A100 PCIe 80GB Tensor Core GPU

Description

The NVIDIA A100 PCIe 80GB Tensor Core GPU is a professional data-center accelerator engineered for demanding AI, machine-learning, HPC, scientific-computing, and data-intensive workloads.

Built on the NVIDIA Ampere architecture, the A100 uses the GA100 GPU and combines high-throughput CUDA computing with specialized Tensor Core acceleration. Its 80GB HBM2e memory provides the capacity required for large neural-network models, massive datasets, scientific simulations, and memory-intensive analytics, while its 1,935GB/s memory bandwidth enables extremely fast movement of data between the GPU and high-bandwidth memory.

The A100 PCIe 80GB delivers up to 19.5 TFLOPS FP32, 9.7 TFLOPS FP64, and 312 TFLOPS FP16/BFLOAT16 Tensor Core performance under NVIDIA’s specified acceleration figures. With structured sparsity, supported Tensor Core workloads can achieve substantially higher effective throughput.

One of its major advantages is Multi-Instance GPU (MIG) technology. The A100 can be partitioned into up to seven isolated GPU instances, each with dedicated resources, allowing multiple workloads, users, or applications to share a single physical accelerator while maintaining workload isolation.

For multi-GPU configurations, the A100 PCIe supports NVIDIA NVLink Bridge connectivity for two GPUs, providing up to 600GB/s of GPU-to-GPU interconnect bandwidth in supported configurations. The card also provides PCIe Gen4 with up to 64GB/s interface bandwidth.

The A100 PCIe 80GB uses a dual-slot, 10.5-inch PCIe card design with a passive heatsink. Because it is passively cooled, it requires adequate chassis airflow and is intended for qualified server platforms rather than conventional desktop workstations. Its maximum thermal design power is 300W.

This makes the A100 PCIe 80GB an excellent accelerator for enterprise AI infrastructure, cloud computing, machine learning, deep-learning training and inference, scientific research, HPC clusters, virtualization, and other workloads requiring substantial GPU memory and computational throughput.

3. Complete Technical Specification

Specification	NVIDIA A100 PCIe 80GB
Product Family	NVIDIA A100 Tensor Core GPU
Architecture	NVIDIA Ampere
GPU	NVIDIA GA100
GPU Memory	80GB HBM2e
Memory Interface	High-Bandwidth Memory
Memory Bandwidth	1,935GB/s
FP64 Performance	9.7 TFLOPS
FP64 Tensor Core	19.5 TFLOPS
FP32 Performance	19.5 TFLOPS
TF32 Tensor Core	156 TFLOPS
TF32 with Sparsity	Up to 312 TFLOPS
BFLOAT16 Tensor Core	312 TFLOPS
BFLOAT16 with Sparsity	Up to 624 TFLOPS
FP16 Tensor Core	312 TFLOPS
FP16 with Sparsity	Up to 624 TFLOPS
INT8 Tensor Core	624 TOPS
INT8 with Sparsity	Up to 1,248 TOPS
MIG Support	Yes
Maximum MIG Instances	Up to 7
MIG Profile Capacity	Up to 10GB per instance
Host Interface	PCI Express
PCIe Generation	PCIe Gen4
PCIe Interface Bandwidth	Up to 64GB/s
GPU Interconnect	NVIDIA NVLink Bridge
NVLink Configuration	Up to 2 PCIe GPUs
NVLink Bandwidth	Up to 600GB/s in supported configurations
Form Factor	PCIe, dual-slot
Card Length	10.5 inches
Cooling	Passive heatsink; requires server airflow
Maximum TDP	300W
Target Platform	Data-center / enterprise servers
GPU Class	Data-center accelerator
Primary Workloads	AI, ML, HPC, analytics, scientific computing

Performance figures above are NVIDIA’s published specifications for the A100 80GB PCIe. Sparsity figures apply to supported workloads and configurations.

4. Applications

The NVIDIA A100 PCIe 80GB is suitable for a wide range of demanding professional and enterprise workloads, including:

Artificial Intelligence (AI)
Machine Learning (ML)
Deep Learning Training
Deep Learning Inference
Large Language Model (LLM) workloads
Generative AI
Natural Language Processing
Computer Vision
Recommendation Systems
High-Performance Computing (HPC)
Scientific Research
Engineering Simulation
Computational Fluid Dynamics
Molecular Dynamics
Seismic Processing
Financial Analytics
Big Data Analytics
Data Science
GPU-accelerated databases
Cloud GPU infrastructure
Virtualized GPU environments
Enterprise AI platforms
Multi-GPU computing clusters

5. Compatibility

The NVIDIA A100 PCIe 80GB is designed for qualified enterprise and data-center server platforms supporting PCIe Gen4 x16-class accelerator configurations.

Platform Requirements

PCIe-compatible server motherboard
PCIe Gen4 support recommended
Adequate chassis airflow for passive GPU cooling
Server power system capable of supporting a 300W accelerator
Appropriate GPU power cabling, according to the specific server implementation
Sufficient physical clearance for a dual-slot, 10.5-inch card
NVIDIA-supported GPU drivers and software stack

NVIDIA specifies the A100 80GB PCIe for partner and NVIDIA-Certified Systems supporting configurations from 1 to 8 GPUs.

Important: The A100 PCIe 80GB is a passively cooled server accelerator, not a conventional consumer/workstation graphics card. Server airflow and platform compatibility should be confirmed before installation.

6. Key Benefits

80GB HBM2e Memory

Provides a large high-bandwidth memory pool for AI models, scientific datasets, simulations, and memory-intensive workloads.

1,935GB/s Memory Bandwidth

Enables extremely high-speed data transfer between compute resources and GPU memory, helping accelerate bandwidth-intensive applications.

Tensor Core Acceleration

Specialized Tensor Cores accelerate AI and matrix-based workloads across FP16, BFLOAT16, TF32, and INT8 precision modes.

Multi-Instance GPU

MIG technology enables the GPU to be divided into up to seven isolated instances, improving resource utilization in shared enterprise and cloud environments.

PCIe Gen4 Connectivity

Provides high-bandwidth host connectivity and makes the A100 PCIe suitable for a broad range of enterprise server platforms.

NVLink Support

Two compatible PCIe A100 GPUs can be connected using NVIDIA NVLink Bridge technology for high-speed GPU-to-GPU communication.

Enterprise-Class Design

The passive dual-slot form factor is optimized for professional server environments where high-density GPU acceleration and controlled airflow are available.