NVIDIA Sets AI Inference Records, Introduces A30 and A10 GPUs for Enterprise Servers

NVIDIA Sets AI Inference Records, Introduces A30 and A10 GPUs for Enterprise Servers

NVIDIA has announced that its AI inference platform, newly  expanded with NVIDIA® A30 and A10 GPUs for mainstream servers, has achieved record-setting  performance across every category on the latest release of MLPerf. 

MLPerf is the industry’s established benchmark for measuring AI performance across a range of  workloads spanning computer vision, medical imaging, recommender systems, speech  recognition and natural language processing.  

Debuting on MLPerf, NVIDIA A30 and A10 GPUs combine high performance with low power  consumption to provide enterprises with mainstream options for a broad range of AI inference,  training, graphics and traditional enterprise compute workloads. Cisco, Dell Technologies,  Hewlett Packard Enterprise, Inspur and Lenovo are expected to integrate the GPUs into their  highest volume servers starting this summer.  

NVIDIA achieved these results taking advantage of the full breadth of the NVIDIA AI platform – encompassing a wide range of GPUs and AI software, including TensorRT™ and NVIDIA Triton™  Inference Server – which is deployed by leading enterprises, such as Microsoft, Pinterest,  Postmates, T-Mobile, USPS and WeChat. 

“As AI continues to transform every industry, MLPerf is becoming an even more important tool  for companies to make informed decisions on their IT infrastructure investments,” said Ian Buck,  general manager and vice president of Accelerated Computing at NVIDIA. “Now, with every 

major OEM submitting MLPerf results, NVIDIA and our partners are focusing not only on  delivering world-leading performance for AI, but on democratising AI with a coming wave of  enterprise servers powered by our new A30 and A10 GPUs.”  

MLPerf Results 

NVIDIA is the only company to submit results for every test in the data centre and edge  categories, delivering top performance results across all MLPerf workloads. 

Several submissions also use Triton Inference Server, which simplifies the complexity of  deploying AI in applications by supporting models from all major frameworks, running on GPUs,  as well as CPUs, and optimising for different query types including batch, real-time and  streaming. Triton submissions achieved performance close to that of the most optimised GPU  implementations, as well as CPU implementations, with comparable configurations.  

NVIDIA also broke new ground with its submissions using the NVIDIA Ampere architecture’s  Multi-Instance GPU capability by simultaneously running all seven MLPerf Offline tests on a single  GPU using seven MIG instances. The configuration showed nearly identical performance  compared with a single MIG instance running alone.  

These submissions demonstrate MIG’s performance and versatility, which enable infrastructure  managers to provision right-sized amounts of GPU compute for specific applications to get  maximum output from every data centre GPU. 

In addition to NVIDIA’s own submissions, NVIDIA partners Alibaba Cloud, Dell Technologies,  Fujitsu, GIGABYTE, HPE, Inspur, Lenovo and Supermicro submitted a total of over 360 results  using NVIDIA GPUs. 

NVIDIA’s Expanding AI Platform 

The NVIDIA A30 and A10 GPUs are the latest additions to the NVIDIA AI platform, which includes  NVIDIA Ampere architecture GPUs, NVIDIA Jetson AGX Xavier™ and Jetson Xavier NX, and a full  stack of NVIDIA software optimised for accelerating AI. 

The A30 delivers versatile performance for industry-standard servers, supporting a broad range  of AI inference and mainstream enterprise compute workloads, such as recommender systems,  conversational AI and computer vision. 

The NVIDIA A10 GPU accelerates deep learning inference, interactive rendering, computer-aided  design and cloud gaming, enabling enterprises to support mixed AI and graphics workloads on a  common infrastructure. Using NVIDIA virtual GPU software, management can be streamlined to  improve the utilisation and provisioning of virtual desktops used by designers, engineers, artists  and scientists. 

The NVIDIA Jetson platform, based on the NVIDIA Xavier™ system-on-module, provides server class AI performance at the edge, enabling a wide variety of applications in robotics, healthcare,  retail and smart cities. Built on NVIDIA’s unified architecture and the CUDA-X™ software stack,  Jetson is the only platform capable of running all the edge workloads in compact designs while consuming less than 30W of power.  


NVIDIA A100 GPUs are available in servers from leading manufacturers and in the cloud from all  major cloud service providers. Additionally, A100 GPUs are featured across the NVIDIA DGX™  systems portfolio, including the NVIDIA DGX Station A100, NVIDIA DGX A100 and NVIDIA DGX  SuperPOD.  

The A30 and A10, which consume just 165W and 150W, are expected in a wide range of servers  starting this summer, including NVIDIA-Certified Systems™ that go through rigorous testing to  ensure high performance across a wide range of workloads.  

The Jetson AGX Xavier and Jetson Xavier NX system-on-module are available from distributors  globally.  NVIDIA Triton and NVIDIA TensorRT are both available on NGC™, NVIDIA’s software catalogue.

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