NVIDIA Extends AI Inference Performance Leadership, with Debut Results on Arm-based Servers 

Sept. 23, 2021 -- NVIDIA delivers the best results in AI inference using either x86 or Arm-based CPUs, according to benchmarks released today.

It’s the third consecutive time NVIDIA has set records in performance and energy efficiency on inference tests from MLCommons, an industry benchmarking group formed in May 2018.

And it’s the first time the data-center category tests have run on an Arm-based system, giving users more choice in how they deploy AI, the most transformative technology of our time.

Tale of the Tape

NVIDIA AI platform-powered computers topped all seven performance tests of inference in the latest round with systems from NVIDIA and nine of our ecosystem partners including Alibaba, Dell Technologies, Fujitsu, GIGABYTE, Hewlett Packard Enterprise, Inspur, Lenovo, Nettrix and Supermicro.

And NVIDIA is the only company to report results on all MLPerf tests in this and every round to date.

Inference is what happens when a computer runs AI software to recognize an object or make a prediction. It’s a process that uses a deep learning model to filter data, finding results no human could capture.

MLPerf’s inference benchmarks are based on today’s most popular AI workloads and scenarios, covering computer vision, medical imaging, natural language processing, recommendation systems, reinforcement learning and more.

So, whatever AI applications they deploy, users can set their own records with NVIDIA.

Why Performance Matters

AI models and datasets continue to grow as AI use cases expand from the data center to the edge and beyond. That’s why users need performance that’s both dependable and flexible to deploy.

MLPerf gives users the confidence to make informed buying decisions. It’s backed by dozens of industry leaders, including Alibaba, Arm, Baidu, Google, Intel and NVIDIA, so the tests are transparent and objective.

Flexing Arm for Enterprise AI

The Arm architecture is making headway into data centers around the world, in part thanks to its energy efficiency, performance increases and expanding software ecosystem.

The latest benchmarks show that as a GPU-accelerated platform, Arm-based servers using Ampere Altra CPUs deliver near-equal performance to similarly configured x86-based servers for AI inference jobs. In fact, in one of the tests, the Arm-based server out-performed a similar x86 system.

NVIDIA has a long tradition of supporting every CPU architecture, so we’re proud to see Arm prove its AI prowess in a peer-reviewed industry benchmark.

“Arm, as a founding member of MLCommons, is committed to the process of creating standards and benchmarks to better address challenges and inspire innovation in the accelerated computing industry,” said David Lecomber, a senior director of HPC and tools at Arm.