HPCwire: NVIDIA Shifts GPU Clusters Into Second Gear

The Leading Source for Global News and Information Covering the Ecosystem of High Productivity Computing

HPCwire >> Features

May 04, 2009

NVIDIA Shifts GPU Clusters Into Second Gear

by Michael Feldman, HPCwire Editor

GPU-accelerated clusters are moving quickly from the "kick the tires" stage into production systems, and NVIDIA has positioned itself as the principal driver for this emerging high performance computing segment.

The company's Tesla S1070 hardware, along with the CUDA computing environment, are starting to deliver real results for commercial HPC workloads. For example Hess Corporation has a 128-GPU cluster that is performing seismic processing for the company. The 32 S1070s (4 GPUs per board) are paired with dual-socket quad-core CPU servers and are performing at the level of about 2,000 dual-socket CPU servers for some of their workloads. For Hess, that means it can get the same computing horsepower for 1/20 the price and for 1/27 the power consumption.

Hess is not alone. Brazilian oil company Petrobas has built a 72-GPU Tesla cluster for its seismic codes. Although the company hasn't released specific performance data, based on preliminary testing, Petrobas expects to see a 5X to 20X improvement compared to a CPU-based cluster platform. Chevron and Total SA are also experimenting with GPU acceleration and although they haven't divulged what types of systems are being used, NVIDIA products are almost certainly in the mix.

BNP Paribas, a French banking firm, is using a Tesla S1070 to compute equity pricing on the derivatives the company tracks. According to Stéphane Tyc, head of the company's Corporate and Investment Banking Division in the GECD Quantitative Research group, they were able to achieve the same performance as 500 CPU cores with just half a Tesla board (two GPUs). Better yet, the platform delivered a 100-fold increase in computations per watt compared to a CPU-only system. "We were actually surprised to get numbers of that magnitude," said Tyc. As of March, BNP Paribas had not deployed the system for live trading, but there are already plans in place to port more software.

Up until now, all of these GPU-accelerated clusters had to be custom-built. In an effort to get a more "out of box" experience for GPU cluster users, NVIDIA has launched its "Tesla GPU Preconfigured Cluster" strategy. Essentially, it's a set of guidelines for OEMs and system builders for NVIDIA-accelerated clusters, the idea being to make GPU clusters as easy to order and install as their CPU-only counterparts. It's basically a parallel strategy to NVIDIA's personal supercomputer workstation program, which the company rolled out in November 2008.

The guidelines consist of a set of hardware and software specs that define a basic GPU cluster configuration. In a nutshell, each cluster has a CPU head node that runs the cluster management software, an InfiniBand switch for node-to-node communication, and four or more GPU-accelerated compute nodes. Each compute node has a CPU server hooked up to a Tesla S1070 via PCI Express. On the software side, a system includes clustering software, MPI, and NVIDIA's CUDA development tools. Most of this is just standard fare, but the cluster software is typically a Rocks roll for CUDA or something equivalent.

NVIDIA itself isn't building any systems. As the company did with personal supercomputing, it has enlisted partner OEMs and distributors to offer GPU-accelerated clusters. The system vendors can add value by selling their own clustering software, tools, services and hardware options. Currently NVIDIA has signed more than a dozen players, including many of the usual HPC suspects: Cray, Appro, Microway, Penguin Computing, Colfax International, and James River Technical. NVIDIA has also corralled some regional workstation and server distributors to attain a more global reach. In this category we have CADNetwork (Germany), E4 (Italy), T-Platforms (Russia), Netweb Technologies (India), Viglen (UK). The complete list of partners is on NVIDIA's Web site.

A bare-bones system -- a head node and four GPU-accelerated servers -- should run about $50,000. That configuration will deliver around 16 (single-precision) teraflops. But larger systems can scale into the 100s of teraflops territory and run $1 million. In this $50K to $1M price range, the systems are aimed at research groups of varying sizes. A low-end 16-GPU machine, for example, could serve a professor and his or her graduate research team, while a 100-GPU system would most likely be shared by multiple research groups spread across an organization.

This reflects how multi-teraflop CPU clusters are used today, but in the case of GPUs, the price point is an order of magnitude lower. NVIDIA's goal is to make this capability available for the hundreds of thousands of researchers who could potentially use this level of computing, but who can't afford a CPU-based system or don't have the power or floor space to accommodate such a machine.

Software will continue to be the limiting factor, since a lot of important technical computing codes are just now being ported to the GPU. CUDA-enabled packages like NAMD (NAnoscale Molecular Dynamics) and GROMACS (GROningen MAchine for Chemical Simulations) are well into development and will soon make their way into commercial systems. In the near future, OpenCL should offer another avenue for porting higher level GPU computing codes. All of this means system builders will increasingly be able to craft turnkey GPU clusters for specific application segments.

If GPU clusters take off, it would be especially welcome news for NVIDIA. Like many chip manufacturers, the company is struggling through the economic downturn. Its revenues declined 16 percent last year, and it recorded its first net loss in a decade. The good news is that in the GPU computing realm, NVIDIA is the clear market leader. And while the company's HPC offerings are not a volume business, if Tesla GPUs become the accelerator of choice for millions of researchers, that could change.

Article Tools

Share Options

(Digg, Technorati, more)

Subscribe

Subscribe to HPCwire

Discussion

There are 0 discussion items posted.

Join the Discussion

You must be a registered user in order to comment on HPCwire stories.

Members enjoy:

	Access to Special Content, including Podcasts, Webcasts, and Whitepapers and more!
	Ability to take an active role in the discussions that are shaping the HPC technology discipline!
	Special offers available only to HPCwire members!

Become a Registered User Today!

Registered Users Log in Here to Comment

Email Address:	Password (case sensitive)

Remember me	Forgot Password?

RSS Feeds

Feeds by Topic

Feeds by Industry

Feeds by Content Type

Top Headlines

Australia Commissions Cray Supercomputer

Mar 19 | OfficialWire | New super to support intelligence work Down Under. Read more...

Intel Partners See 'Easy' Upgrade Path With Xeon 5600 Chips

Mar 18 | ChannelWeb | Westmere parts already showing up in HPC machines. Read more...

AMD: OEMs primed for Opteron 6100s

Mar 17 | The Register | But what about the tier ones? Read more...

Arrival of the Desktop Supercomputer

Mar 17 | Cadalyst Magazine | A new generation of workstations is changing the nature of technical computing. Read more...

Scheduling HPC In The Cloud

Mar 17 | Linux Magazine | Latest iteration of Sun Grid Engine able to tap into Cloud. Read more...

Read more headlines...

Featured Whitepapers

Virtualization for Aggregation And The vSMP Architecture™

Jan 12 | | In-depth look at vSMP Foundation server virtualization technology, technical implementation, use cases and capabilities. The technical whitepaper provides an architectural overview and details on the three vSMP Foundation products: vSMP Foundation for SMP, vSMP Foundation for Cluster and vSMP Foundation for Cloud.

Copper Cable Technologies for High Performance Computing

Jan 18 | | This white paper discusses Gore’s copper cable assemblies, and how they continue to exceed the standards for providing reliable, cost-effective solutions for high-performance computer applications.

View the White Paper Library

Multimedia

Webcast: Virtualized Data Center Roundtable

Join this online panel discussion for live Q&A with leading industry experts, analysts, and end-users to discuss the latest innovations, best practices, barriers to implementation, and measurable benefits of server virtualization with a particular focus on today's real world solutions.

Webcast: Watch SC09 Birds of a Feather Video: Scalable Fault-Tolerant HPC Supercomputers

Learn about scalable fault-tolerant architectures and examples of energy efficient and scalable supercomputing clusters using dual QDR InfiniBand to combine capacity computing with network failover capabilities with the help of programming languages such as MPI and a robust Linux cluster management package.

Webcast: High Performance Computing for a Smarter Planet

LIVE@SCO9: The IBM team discusses new innovations in hardware, software and services that help clients better understand their workloads and get insight from their R&D efforts. Technology demonstrations include the soon-to-be-released Power7 HPC processor, the DCS990 system with 2.4 petabytes of storage, the xCAT management tool, secure HPC cloud computing and more. Winners of two HPCwire Readers' and Editors’ Choice Awards! Take the IBM virtual tour at SC09 or more information go online to: http://www-03.ibm.com/systems/deepcomputing/sc09.html