NVIDIA Pitches GPU Computing in the Cloud

By Michael Feldman

October 21, 2009

At the Web 2.0 Summit in San Francisco this week, NVIDIA announced a GPU-powered 3D Web platform. Called the NVIDIA RealityServer, it consists of Tesla GPUs, rendering software and a Web service environment, all integrated into a platform designed to deliver photorealistic image streams via a cloud computing model. The new offering is yet another example of how the company intends to push its high-end GPUs into CPU territory.

The basic idea behind RealityServer is to do all the heavy computation lifting of image rendering on the server side, such that photorealistic 3D content can be delivered interactively across the Web. That means mass-market devices from smart phones to desktops and everything in between can be used to do high-end imaging. Applications include architectural design, product design, manufacturing and apparel styling, as well as HPC visual applications in such areas as oil and gas, medical diagnostics, and scientific research. As a result, potential users span the entire population: consumers, artists, product designers, doctors, architects, engineers, and scientists.

The big emphasis here is on photorealistic images. Generating such content is extremely compute intensive since the software must calculate the effects of light bouncing off the objects in a scene. Rendering a single photorealistic frame for a complex image can take a whole day on a typical CPU-based workstation. So unless one happens to own a deskside HPC machine (which may themselves contain NVIDIA GPUs), client-side processing is usually not able to deliver this interactive user experience.

Significantly, NVIDIA is not yet claiming this can be used to deliver photorealistic animation. For that to happen, presumably gamers and graphics animators will have to wait until GPU horsepower increases to the point where real-time photorealistic animation is practical. Theoretically, someone could build a big enough GPU cluster to do this today (or with Fermi GPUs next year), but computing 60 photorealistic frames per second is not likely to be economically feasible in the near term.

The critical 3D software component of RealityServer is iray, a photorealistic rendering technology developed by mental images, an NVIDIA subsidiary the company bought two years ago. The iray software is essentially a GPU-accelerated rendering mode of its flagship mental ray product. The iray software uses global illumination, which requires a lot more computational horsepower than garden variety ray-tracing (which usually only approximates global illumination or just uses direct illumination). True global illumination, however, blends the effect of direct and indirect light and will produce a much more refined image, almost indistinguishable from a photograph. Rolf Herken, founder, CEO and CTO of mental images, characterized iray as “the first physically correct renderer.”

Photorealistic image

In this case, the quality of the image is dependent on the fidelity of the input data rather than the algorithm. The feature that makes this practical in a cloud environment is iray’s ability to scale across many GPUs. According to the iray FAQ (PDF), the software scales “completely linearly on a local system, almost linearly on RealityServer across multiple machines.”

The RealityServer software itself encompasses the iray renderer as well as the rest of the software stack that turns 3D imaging into a Web service. OpenGL is also supported for situations where iray computation would be too slow to deliver interactive rendering. As one might suspect, RealityServer includes support for standard CAD and digital content creation formats and can run under both Linux or Windows.

The hardware environment for RealityServer is NVIDIA’s new Tesla RS platform, which comes in medium (8-31 GPUs), large (32-99 GPUs), and extra-large (100-plus GPUs) configurations. The Tesla device was presumably used since the high-end graphics chip and the larger memory capacity is specifically aimed at big GPU computing workloads. The smallest RS configuration is aimed at workgroups (for example, a group of collaborating architects), while the largest configuration is designed for thousands of concurrent users. This is only a general guideline, since some applications, like medical or oil & gas imaging, require multiple GPUs per user, while others, such as online entertainment, can support many users with a just single GPU.

NVIDIA is pointing interested parties who want to build RealityServer GPU server infrastructure to its OEM partners (which include HPC vendors Colfax, Appro, and Penguin Computing), but is not indicating which manufacturers are actually offering these configurations today. The RealityServer software itself will be available on Nov. 30, when a developer edition will be made available free of charge, including the right to deploy non-commercial applications. No mention was made of licensing RealityServer or iray for commercial applications.

As far as who will end up offering RealityServer infrastructure, NVIDIA is hoping public cloud providers, like for example Amazon, will be interested in adding this capability into their offerings. Private GPU clouds are also on the table, and frankly, are the more likely scenario in the short term, since I’m guessing a critical mass of RealityServer applications will need to be developed for the big cloud providers to be interested. In the NVIDIA press release, there were a handful of comments from some initial RealityServer customers, including mydeco.com, SceneCaster, and Wichita State University’s Virtual Reality Center at the National Institute for Aviation Research. Undoubtably, there is more low-hanging fruit out there waiting to be picked.

The ease of developing these RealityServer applications will likely portend the success of the business in general. Users, of course, may be squeamish about locking their software to a specific vendor’s platform, but with no competing offering currently on the market, the choice may become simple. And if NVIDIA supports RealityServer efforts in the same manner it is using to develop the CUDA ecosystem, the company may indeed have a winning model for GPU computing in the cloud.

Subscribe to HPCwire's Weekly Update!

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

Study Identifies Best Practices for Public-Private HPC Engagement

August 22, 2017

What's the best way for HPC centers in the public sphere to engage with private industry partners to boost the competitiveness of the companies and the larger communities? That question is at the heart of a new study pub Read more…

By Tiffany Trader

Google Launches Site to Share its NYC-based Algorithm Research

August 22, 2017

Much of Google’s algorithm development occurs in groups scattered throughout New York City. Yesterday, Google launched a single website - NYC Algorithms and Optimization Team page - to provide a deeper view into all of Read more…

By John Russell

Dell Strikes Reseller Deal with Atos; Supplants SGI

August 22, 2017

Dell EMC and Atos announced a reseller deal today in which Dell will offer Atos’ high-end 8- and 16-socket Bullion servers. Some move from Dell had been expected following Hewlett Packard Enterprise’s purchase of SGI Read more…

By John Russell

HPE Extreme Performance Solutions

Leveraging Deep Learning for Fraud Detection

Advancements in computing technologies and the expanding use of e-commerce platforms have dramatically increased the risk of fraud for financial services companies and their customers. Read more…

Glimpses of Today’s Total Solar Eclipse

August 21, 2017

Here are a few arresting images posted by NASA of today’s total solar eclipse. Such astronomical events have always captured our imagination and it’s not hard to understand why such occurrences were often greeted wit Read more…

By John Russell

Study Identifies Best Practices for Public-Private HPC Engagement

August 22, 2017

What's the best way for HPC centers in the public sphere to engage with private industry partners to boost the competitiveness of the companies and the larger c Read more…

By Tiffany Trader

Tech Giants Outline Battle Plans for Future HPC Market

August 21, 2017

Four companies engaged in a cage fight for leadership in the emerging HPC market of the 2020s are, despite deep differences in some areas, in violent agreement Read more…

By Doug Black

Microsoft Bolsters Azure With Cloud HPC Deal

August 15, 2017

Microsoft has acquired cloud computing software vendor Cycle Computing in a move designed to bring orchestration tools along with high-end computing access capabilities to the cloud. Terms of the acquisition were not disclosed. Read more…

By George Leopold

HPE Ships Supercomputer to Space Station, Final Destination Mars

August 14, 2017

With a manned mission to Mars on the horizon, the demand for space-based supercomputing is at hand. Today HPE and NASA sent the first off-the-shelf HPC system i Read more…

By Tiffany Trader

AMD EPYC Video Takes Aim at Intel’s Broadwell

August 14, 2017

Let the benchmarking begin. Last week, AMD posted a YouTube video in which one of its EPYC-based systems outperformed a ‘comparable’ Intel Broadwell-based s Read more…

By John Russell

Deep Learning Thrives in Cancer Moonshot

August 8, 2017

The U.S. War on Cancer, certainly a worthy cause, is a collection of programs stretching back more than 40 years and abiding under many banners. The latest is t Read more…

By John Russell

IBM Raises the Bar for Distributed Deep Learning

August 8, 2017

IBM is announcing today an enhancement to its PowerAI software platform aimed at facilitating the practical scaling of AI models on today’s fastest GPUs. Scal Read more…

By Tiffany Trader

IBM Storage Breakthrough Paves Way for 330TB Tape Cartridges

August 3, 2017

IBM announced yesterday a new record for magnetic tape storage that it says will keep tape storage density on a Moore's law-like path far into the next decade. Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Leading Solution Providers

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

IBM Clears Path to 5nm with Silicon Nanosheets

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a proces Read more…

By Tiffany Trader

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This