NVIDIA A2
GPU architecture NVIDIA Ampere
Compact GPU accelerator for computing and graphics
1280 NVIDIA CUDA cores for parallel computing
40 Tensor cores to accelerate AI and deep learning computing
16 GB of GPU memory to support AI models and analytics applications
Memory capacity up to 200 GB/s
Interface PCIe 4.0 x16 for high-speed data transfer
Passive cooling designed for servers and edge systems
Very low power consumption: 40-60 watts - ideal for high-density GPU systems
Free shipping from €300
Promocja cenowa na model HDR-15-5
Product intended for professional use only
NVIDIA A2
Description
NVIDIA A2 - an energy-efficient GPU accelerator for AI at the edge of the network
NVIDIA A2 Tensor Core GPU is a compact accelerator designed to accelerate artificial intelligence computing in space-constrained environments with low energy budgets. The card is based on NVIDIA Ampere architecture and provides efficient AI inference (AI inference) models in edge servers, data centres, and industrial systems.
With its low-profile PCIe Gen4 design and configurable power consumption of 40-60 W, NVIDIA A2 is ideal for high-density GPU servers, edge computing systems, and continuous AI platforms.
NVIDIA Ampere architecture for AI computing
The A2GPU features 1280 CUDA cores and 40 Tensor cores to accelerate mathematical operations used in machine learning and deep learning systems. As a result, the accelerator enables efficient processing of AI models without the need for large and power-hungry data centre GPUs.
The card offers 16 GB of GPU memory with a bandwidth of up to 200 GB/s to support artificial intelligence models and analytical applications requiring processing of large data streams.
AI inference and real-time data analytics
NVIDIA A2 is specifically optimised for inference of AI models in production environments. The accelerator allows for fast processing of deep learning models and real-time data analysis.
TheGPU finds applications in, among others:
- image analysis and vision AI systems
- intelligent video analysis (video analytics)
- security and surveillance systems
- LLLM model inference and conversational systems
- RAG (Retrieval Augmented Generation)
- IoT data analysis
Ideal for edge AI systems
With its small footprint, passive cooling and low power consumption, the NVIDIA A2 can be installed in a wide range of edge servers, industrial PCs and data processing systems close to the source.
The accelerator is used in solutions such as:
- edge computing in industry
- video analytics in smart cities
- autonomous systems and robotics
- AI platforms in commerce and logistics
- distributed data processing systems
Technical Specification
| Peak FP32 | 4.5 TF |
|---|---|
| TF32 Tensor Core | 9 TF | 18 TF¹ |
| BFLOAT16 Tensor Core | 18 TF | 36 TF¹ |
| Peak FP16 Tensor Core | 18 TF | 36 TF¹ |
| Peak INT8 Tensor Core | 36 TOPS | 72 TOPS¹ |
| Peak INT4 Tensor Core | 72 TOPS | 144 TOPS¹ |
| RT Cores | 10 |
| Media Engines | 1 video encoder, 2 video decoders (includes AV1 decode) |
| GPU Memory | 16 GB GDDR6 |
| GPU Memory Bandwidth | 200 GB/s |
| Interconnect | PCIe Gen4 x8 |
| Form Factor | 1-slot, low-profile PCIe |
| Max Thermal Design Power (TDP) | 40–60 W (configurable) |
| Virtual GPU (vGPU) Software Support² | NVIDIA Virtual PC (vPC), NVIDIA Virtual Applications (vApps), NVIDIA RTX Virtual Workstation (vWS), NVIDIA AI Enterprise, NVIDIA Virtual Compute Server (vCS) |
¹ With sparsity
² Supported in future vGPU release
