Nvidia A2 Hosting

Dedicated Nvidia A2 Hosting Pricing

Nvidia A2 pairs with Dual 10-Core E5-2660v2 and 128GB RAM accelerating your business workloads from AI reasoning to edge computing.
Professional GPU Server

Nvidia A2

Entry-level AI reasoning and edge computing accelerator based on ampere architecture.
CUDA Cores: 1280
GPU Memory: 16GB
Performance: 4.5 TFLOPS
128GB RAM
Dual 10-Core E5-2660v2
240GB SSD + 960GB SSD
100Mbps Unmetered Bandwidth
$ 199.00/m

Purchase a Computer with GPU VS. Rent a GPU Server

Which one suits you better?
Purchasing GPUs
  • Excellent when equipped with adequate hardware
  • Expensive
  • Need extra cost when updating
  • Once your research or project ends, you may be left with a high-powered machine with nothing to do.
  • You cannot guarantee that your local computer will be turned on 24 hours a day, nor can you resist an unexpected power outage that may cause your machine to fail.
Renting GPUs
  • High performance as local GPU Servers
  • Low Cost
  • Managed by hosting provider
  • GPU instance can be turned on or off at any time, and upgrade or downgrade depending on your hardware needs.
  • 99.9% uptime and 24*7 expert hardware monitoring ensure the stable operation of your applications and services, so that your users can have a better experience.

Nvidia A2 Specifications & Benchmark

GPU dedicated server equipped with the Entry-level AI reasoning and edge computing accelerator.
Specifications
GPU Microarchitecture Ampere
CUDA Cores 1280
TDP 60W
Memory Bus Width 128 bit
Memory Clock Speed 6251 MHz
Memory Bandwidth 200 GB/s
Memory 16GB GDDR6 with ECC
System Interface PCI Express Gen 4 x 8
GPU Clock speed 1770 MHz
Performance 4.5 TFLOPS
GeekBench 5 OpenCL 36484

GPU Features in Nvidia A2 Hosting Server

Featuring a low-profile PCIe Gen4 card and a low 40–60 watt (W) configurable thermal design power (TDP) capability, the A2 brings versatile inference acceleration to any server.

Third-Generation Tensor Cores

The third-generation Tensor Cores in A2 support integer math, down to INT4, and floating-point math, up to FP32, to deliver high AI training and inference performance. The NVIDIA Ampere architecture also supports TF32 and NVIDIA’s automatic mixed precision (AMP) capabilities.

Root of Trust Security

Providing security in edge deployments and end-points is critical for enterprise business operations. A2 offers secure boot through trusted code authentication and hardened rollback protections to protect against malicious malware attacks.

Second-Generation RT Cores

The NVIDIA A2 GPU includes dedicated RT Cores for ray tracing and Tensor Cores for AI to power groundbreaking results at breakthrough speed. It delivers up to 2x the throughput over the previous generation and the ability to concurrently run ray tracing with either shading or denoising capabilities.

Hardware Transcoding Performance

Exponential growth in video applications demands real-time scalable performance, requiring the latest in hardware encode and decode capabilities. A2 GPUs use dedicated hardware to fully accelerate video decoding and encoding for the most popular codecs, including H.265, H.264, VP9, and AV1 decode.

What are Nvidia A2 Servers Mostly used for?

Nvidia A2 is designed for entry-level inference tasks, and thanks to its relatively small size and low power consumption, is also being aimed at edge computing scenarios as well.

AI Inference Acceleration

AI inference is deployed to enhance consumer lives with smart, real-time experiences and to gain insights from trillions of end-point sensors and cameras. Compared to CPU-only servers, edge and entry-level servers with NVIDIA A2 Tensor Core GPUs offer up to 20X more inference performance, instantly upgrading any server to handle modern AI.

Edge Acceleration

Servers equipped with NVIDIA A2 GPUs offer up to 1.3X more performance in intelligent edge use cases, including smart cities, manufacturing, and retail. NVIDIA A2 GPUs running IVA workloads deliver more efficient deployments with up to 1.6X better price-performance and 10 percent better energy efficiency than previous GPU generations.

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