industry news
Subscribe Now

NVIDIA Turing GPUs and NVIDIA Xavier Achieve Fastest Results on MLPerf Benchmarks Measuring Data Center and Edge AI Inference Performance

NVIDIA today posted the fastest results on new benchmarks measuring the performance of AI inference workloads in data centers and at the edge — building on the company’s equally strong position in recent benchmarks measuring AI training.

The results of the industry’s first independent suite of AI benchmarks for inference, called MLPerf Inference 0.5, demonstrate the performance of NVIDIA Turing™ GPUs for data centers and NVIDIA Xavier™ system-on-a-chip for edge computing.

MLPerf’s five inference benchmarks — applied across a range of form factors and four inferencing scenarios — cover such established AI applications as image classification, object detection and translation.

NVIDIA topped all five benchmarks for both data center-focused scenarios (server and offline), with Turing GPUs providing the highest performance per processor among commercially available entries1. Xavier provided the highest performance among commercially available edge and mobile SoCs under both edge-focused scenarios (single-stream and multi-stream)2.

“AI is at a tipping point as it moves swiftly from research to large-scale deployment for real applications,” said Ian Buck, general manager and vice president of Accelerated Computing at NVIDIA. “AI inference is a tremendous computational challenge. Combining the industry’s most advanced programmable accelerator, the CUDA-X suite of AI algorithms and our deep expertise in AI computing, NVIDIA can help data centers deploy their large and growing body of complex AI models.”

Watch a video of Buck discussing the MLPerf inference benchmarks: https://youtu.be/G3nsTSPY4LI

Highlighting the programmability and performance of its computing platform across diverse AI workloads, NVIDIA was the only AI platform company to submit results across all five MLPerf benchmarks. In July, NVIDIA won multiple MLPerf 0.6 benchmark results for AI training, setting eight records in training performance.

NVIDIA GPUs accelerate large-scale inference workloads in the world’s largest cloud infrastructures, including Alibaba Cloud, AWS, Google Cloud Platform, Microsoft Azure and Tencent. AI is now moving to the edge at the point of action and data creation. World-leading businesses and organizations, including Walmart and Procter & Gamble, are using NVIDIA’s EGX edge computing platform and AI inference capabilities to run sophisticated AI workloads at the edge.

All of NVIDIA’s MLPerf results were achieved using NVIDIA TensorRT™ 6 high-performance deep learning inference software that optimizes and deploys AI applications easily in production from the data center to the edge. New TensorRT optimizations are also available as open source in the GitHub repository.

New Jetson Xavier NX
Expanding its inference platform, NVIDIA today introduced Jetson Xavier NX, the world’s smallest, most powerful AI supercomputer for robotic and embedded computing devices at the edge. Jetson Xavier NX is built around a low-power version of the Xavier SoC used in the MLPerf Inference 0.5 benchmarks.

  1. MLPerf v0.5 Inference results retrieved from www.mlperf.org on Nov. 6, 2019, from entries Inf-0.5-15, Inf-0. 5-16, Inf-0.5-19, Inf-0.5-21. Inf-0.5-22, Inf-0.5-23, Inf-0.5-27. Per-processor performance is calculated by dividing the primary metric of total performance by number of accelerators reported.
  2. MLPerf v0.5 Inference results retrieved from www.mlperf.org on Nov. 6, 2019, from entries Inf-0.5-24, Inf-0.5-28, Inf-0.5-29.

About NVIDIA
NVIDIA’s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at http://nvidianews.nvidia.com/.

Leave a Reply

featured blogs
May 18, 2022
Learn how award-winning ARC processor IP powers automotive functional safety tech, from automotive sensors to embedded vision systems, alongside AI algorithms. The post Award-Winning Processors Drive Greater Intelligence and Safety into Autonomous Automotive Systems appeared...
May 18, 2022
The Virtuoso Education Kit has just been released and now there is already a new kit available: The Organic Printed Electronics PDK Education Kit ! This kit also uses Virtuoso as the main Cadence... ...
May 12, 2022
By Shelly Stalnaker Every year, the editors of Elektronik in Germany compile a list of the most interesting and innovative… ...
Apr 29, 2022
What do you do if someone starts waving furiously at you, seemingly delighted to see you, but you fear they are being overenthusiastic?...

featured video

Increasing Semiconductor Predictability in an Unpredictable World

Sponsored by Synopsys

SLM presents significant value-driven opportunities for assessing the reliability and resilience of silicon devices, from data gathered during design, manufacture, test, and in-field. Silicon data driven analytics provide new actionable insights to address the challenges posed to large scale silicon designs.

Learn More

featured paper

Intel Agilex FPGAs Deliver Game-Changing Flexibility & Agility for the Data-Centric World

Sponsored by Intel

The new Intel® Agilex™ FPGA is more than the latest programmable logic offering—it brings together revolutionary innovation in multiple areas of Intel technology leadership to create new opportunities to derive value and meaning from this transformation from edge to data center. Want to know more? Start with this white paper.

Click to read more

featured chalk talk

Energy Storage: The Key to Sector Coupling

Sponsored by Mouser Electronics and Phoenix Contact

Climate change is making better energy storage more important than ever before. In this episode of Chalk Talk, Dr. Rüdiger Meyer from Phoenix Contact joins me to discuss the what, where and how of energy storage systems. We take a closer look at the structure and components included in typical energy storage systems and the role that connectors play in successful energy storage systems.

Click here for more information about Phoenix Contact Energy Storage Solutions