Nvidia Accelerates AI Inference in the Datacenter with T4 GPU

By George Leopold

September 14, 2018

Nvidia is upping its game for AI inference in the datacenter with a new platform consisting of an inference accelerator chip–the new Turing-based Tesla T4 GPU–and a refresh of its inference server software packaged as a container-based microservice.

The GPU leader also this week announced a new robotics effort centered around an AI platform for autonomous machines along with rollout of a new AI-driven health care platform.

The TensorRT inference platform consists of Nvidia’s latest GPU, the Tesla T4, based on its Turing architecture, the chipmaker said Thursday (Sept. 13). The T4 is the successor to the P4 Pascal-based chips, introduced two years ago almost to the day. Peak performance for the refreshed chip (which has 320 Turing Tensor Cores and 2,560 CUDA cores) is 8.1 teraflops of single-precision performance, 65 teraflops of mixed-precision, 130 teraops of INT8 and 260 teraops of INT4 performance. The T4 sits on a low-profile (half-height, half-width) 75 watt PCI-e card.

The other components of the AI platform include real-time inference server software and runtime engine dubbed TensorRT 5 designed to boost neural network performance. The TensorRT server is a container-based microservice designed to allow applications to use AI models within datacenters.

The new inference platform is an attempt to address “the difficulties in deploying datacenter inference,” explained, Ian Buck, vice president of Nvidia’s accelerated computing business unit. Among the performance issues are overused systems while other components are underutilized for inference, Buck added.

The goal is to help accelerate inference in the datacenter. Hence, Nvidia claims its combination of AI hardware and software can process queries 40 times faster than datacenter CPUs.

Meanwhile, the TensorRT 5 inference engine that supports the Turing cores aims to expand the set of trained neural networks running in datacenters to accelerate production workloads. That capability would help deliver, for example, better recommendations in response to queries.

The datacenter platform would offer inference acceleration for visual search, video analysis, targeted advertising and recommendation services that are swamping enterprise datacenters. “This is why they call hyperscale [datacenters] ‘hyperscale’,” Buck noted.

Nvidia estimates the market for AI inference centered around the deployment of neural networks in datacenters delivering live video, speech recognition and product recommendations could soar to $20 billion over the next five years.

Nvidia also joins a growing list of chip and software vendors embracing datacenter microservices as a way to accelerate the delivery of distributed applications. The company’s inference server software allows applications to use AI models in production while boosting GPU utilization and, ultimately, datacenter performance for delivering a range of AI-based services.

Along with supporting most AI frameworks and models, Nvidia said its inference server is integrated with Docker containers and the Kubernetes cluster orchestrator. The inference server is available on Nvidia GPU cloud container registry. Those GPU-accelerated containers are used to package deep learning software as well as HPC applications and visualizations.

Source: Nvidia

Google said this week it would offer early access to T4 GPUs on its cloud platform. Support is also expected from the usual system makers–HPE, IBM, Dell EMC, Fujitsu, Cisco, Oracle and SuperMicro–by year’s end.

Nvidia also this week announced a developer kit for the next wave of robotics. The Jetson AGX Xavier platform targets next-generation autonomous machines that could be used for industrial and manufacturing applications ranging from bridge inspections to package delivery via drones. The AGX kit that includes an embedded AI processor and a software stack was released during a company event this week in Tokyo. Nvidia also announced partnerships with several Japanese manufacturers to develop next-generation autonomous machines.

Rob Csongor, Nvidia’s vice president for autonomous machines, said the AI platform is aimed at the $250 billion robotics market. The AGX platform would “enable broad development across a variety of industries,” Csongor added.

The AGX family also is being extended to include development of future AI-based medical devices. The Clara AGX platform released this week is based on Nvidia’s Xavier AI computing module and Turing GPUs. It targets early detection, diagnostics and treatment.

Kimberly Powell of Nvidia’s health care unit said the Clara developer kit addresses the disconnect between legacy diagnostic tools such as medical imagers and the current shortfall in running modern applications. The Clara framework would allow those tools to connect with GPU servers, boosting their capacity to process raw instrument data and imagery.

Powell said Nvidia is working with GE Healthcare, Mayo Clinic and other major medical providers.

Tiffany Trader contributed to this report.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from its predecessors, including the red-hot H100 and A100 GPUs. Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. While Nvidia may not spring to mind when thinking of the quant Read more…

2024 Winter Classic: Meet the HPE Mentors

March 18, 2024

The latest installment of the 2024 Winter Classic Studio Update Show features our interview with the HPE mentor team who introduced our student teams to the joys (and potential sorrows) of the HPL (LINPACK) and accompany Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the field was normalized for boys in 1969 when the Apollo 11 missi Read more…

Apple Buys DarwinAI Deepening its AI Push According to Report

March 14, 2024

Apple has purchased Canadian AI startup DarwinAI according to a Bloomberg report today. Apparently the deal was done early this year but still hasn’t been publicly announced according to the report. Apple is preparing Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimization algorithms to iteratively refine their parameters until Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimizat Read more…

PASQAL Issues Roadmap to 10,000 Qubits in 2026 and Fault Tolerance in 2028

March 13, 2024

Paris-based PASQAL, a developer of neutral atom-based quantum computers, yesterday issued a roadmap for delivering systems with 10,000 physical qubits in 2026 a Read more…

India Is an AI Powerhouse Waiting to Happen, but Challenges Await

March 12, 2024

The Indian government is pushing full speed ahead to make the country an attractive technology base, especially in the hot fields of AI and semiconductors, but Read more…

Charles Tahan Exits National Quantum Coordination Office

March 12, 2024

(March 1, 2024) My first official day at the White House Office of Science and Technology Policy (OSTP) was June 15, 2020, during the depths of the COVID-19 loc Read more…

AI Bias In the Spotlight On International Women’s Day

March 11, 2024

What impact does AI bias have on women and girls? What can people do to increase female participation in the AI field? These are some of the questions the tech Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Analyst Panel Says Take the Quantum Computing Plunge Now…

November 27, 2023

Should you start exploring quantum computing? Yes, said a panel of analysts convened at Tabor Communications HPC and AI on Wall Street conference earlier this y Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Training of 1-Trillion Parameter Scientific AI Begins

November 13, 2023

A US national lab has started training a massive AI brain that could ultimately become the must-have computing resource for scientific researchers. Argonne N Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire