SGI Colors New Shared Memory Machines Ultraviolet

By Michael Feldman

November 16, 2009

After what may be the longest development cycle ever for a supercomputer, SGI has unveiled the first commercial implementation of its Ultraviolet architecture. The company first announced “Project Ultraviolet” at SC03. Now six years later, it has launched Altix UV, the company’s first scale-up HPC system based on x86 technology. The Altix UV’s connection to the 2003 design is tenuous at best, but the new architecture does fulfill Ultraviolet’s original promise of delivering a shared memory architecture able to scale from a few sockets all the way up to a petascale supercomputer.

SGI Altix UV

Besides being simpler to program than distributed memory clusters, shared memory systems are especially well suited to I/O bound and memory-bound applications; codes that depend upon a lot of inter-processor communication; and any type of application that uses large — as in terabyte-sized — in-memory databases. These shared memory systems can also be used in conjunction with large clusters to provide an “analysis supernode.”

The two initial products, the Altix UV 1000 and Altix UV 100, are both based on Intel Nehalem-equipped blades, which are hooked together with SGI’s 5th generation NUMAlink fabric. The software stack includes everything from the OS on up, including the SGI Foundation Software, data management packages (XFS, CXFS, DMF), SGI’s ProPack and System Management tools, job schedulers (Altair PBSP and Moab) and developer tools and libraries. The machines come with either SUSE Linux Enterprise Server or Red Hat Enterprise Linux.

The blades themselves contain two eight-core Nehalem EX chips, each with a bank of four DDR3 memory channels. If a larger memory to core ratio is desired, there are 6- and 4-core options, as well as a single-socket configuration. An optional I/O riser allows for a choice of expansion slots or external I/O ports. Up to two PCIe slots are available on each blade and these can be used to plug in external storage (SGI or otherwise) or GPGPUs.

SGI’s secret sauce is the UV hub, which sits on each blade and acts as the node controller. The hub, along with the NUMAlink 5 interconnect, is the technology that makes the supersized shared memory possible. The new interconnect delivers sub-microsecond latencies and 15.0 GB/sec of aggregate bandwidth per blade. The hub itself manages data traffic between the local CPU resources and the rest of the system, arbitrating between the local QuickPath Interconnect (QPI) links and the NUMAlink fabric.

According to Jill Matzke, Altix product manager, the SGI engineers decided to limit themselves to two sockets per blade in order to avoid overtaxing the QPI bandwidth, which needs to feed the NUMAlink fabric and I/O. Since Nehalem EX is designed to support up to 8 sockets per board, one might wonder why SGI didn’t opt for the dual-socket-capable Nehalem EP chips. Apparently, EX was chosen because it offered more QPI and memory bandwidth, both of which were essential to the UV design. In any case, the Nehalem EP design does not lend itself to external node controllers, such as the UV hub.

The Altix UV 100 is aimed at the mid-range market, scaling from a single 3U rackmount unit containing two dual-socket blades, up to a 7 teraflop, 96-socket machine that fits into a couple of racks. The upper limit on memory capacity on this product is 6 TB. The UV 100 is aimed at users who need a moderate to large SMP environment for their x86 applications. At the maximum 96-socket configuration, 768 cores are available, which doubles to 1,536 threads thanks to Nehalem-style multithreading support.

The Altix UV 1000 is a cabinet solution that scales all the way to the top, that is, 256 sockets (yielding 2,048 cores or 4,096 threads) and 16 TB of memory. At the max configuration, this model delivers 18.6 peak teraflops in a 42U space. The 16 TB limit on the UV 1000 corresponds to the maximum memory reach of the Intel Nehalem processor. However, the UV 1000 design can actually scale beyond this limit by connecting multiple 256-socket systems in a 2-D torus topology. In this case, the system would be partitioned with multiple OS images but support a much larger shared global address space — up into petabytes. The upper limit supported by the UV hub is 32,768 sockets, which would equate to about 2 petaflops. SGI is certainly willing to help interested parties develop such systems, but the vast majority of customers will be able to fit their applications within the 256-socket, single system image machine.

Note the current Itanium-based Altix 4700 reaches to 128 GB because that CPU’s memory address is wider, although core count on those systems tops out at 1024. That said, just getting a handful of terabytes of global memory on an x86 platform is likely to be a big attraction for HPC users. “We are seeing people ordering many more terabytes of memory on UV than they ever did on Altix with Itanium, simply because of the overall capability and the price-performance,” says Matzke.

Although UV supports highly-scaled applications in a global memory model, today the majority of global memory applications scale to just 32 or maybe 64 threads. However, UV, like most shared memory machines, can also deliver great performance for MPI applications by properly exploiting the unified memory and the speed of the interconnect fabric. Moreover, an MPI offload engine has been incorporated into the UV hub to further accelerate this class of applications. SGI has demonstrated a 3X improvement in the HPCC GUPS benchmark with the offload engine enabled. According to Matzke, “70 percent of the people that buy these systems are running MPI, but have other application demands that make it really shine on this kind of an architecture.”

According to Geoffrey Noer, SGI’s senior director of product marketing, the company is currently taking orders for the new UV machines, with the first shipments expected by second quarter of 2010 (following Intel’s release of the Nehalem EX CPUs). Initial customers include the University of Tennessee (1024 cores, 4 TB memory), the North German Supercomputing Alliance, known as HLRN (two systems, 4,352 cores, 18 TB memory), CALMIP in France (128 cores, 1 TB memory), and the University of Hokkaido (180 cores, 360 GB memory). A number of UV systems have also been purchased by the federal government for certain “defense applications” (which shall remain nameless). SGI is not making UV pricing public, but potential buyers can always obtain a quote under NDA.

Although many customers using Itanium Altix systems will undoubtedly transition to the x86 UV platform, Noer says SGI will continue to offer the Altix 450 and 4700 systems. And even though they are not publicly divulging specific plans for future Itanium-based shared memory machines, Noer did have this to offer: “It’s important not to look at Altix UV as a direct replacement for the 4700…. We are working with Intel on next-generation processor technologies as well.  For those customers that are getting the benefits out of the larger address space and benefits with the 4700, they absolutely don’t need to switch to Altix UV.”

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!

Exascale Computing Project Names Doug Kothe as Director

September 20, 2017

The Department of Energy’s Exascale Computing Project (ECP) has named Doug Kothe as its new director effective October 1. He replaces Paul Messina, who is stepping down after two years to return to Argonne National L Read more…

Takeaways from the Milwaukee HPC User Forum

September 19, 2017

Milwaukee’s elegant Pfister Hotel hosted approximately 100 attendees for the 66th HPC User Forum (September 5-7, 2017). In the original home city of Pabst Blue Ribbon and Harley Davidson motorcycles the agenda addresse Read more…

By Merle Giles

NSF Awards $10M to Extend Chameleon Cloud Testbed Project

September 19, 2017

The National Science Foundation has awarded a second phase, $10 million grant to the Chameleon cloud computing testbed project led by University of Chicago with partners at the Texas Advanced Computing Center (TACC), Ren Read more…

By John Russell

HPE Extreme Performance Solutions

HPE Prepares Customers for Success with the HPC Software Portfolio

High performance computing (HPC) software is key to harnessing the full power of HPC environments. Development and management tools enable IT departments to streamline installation and maintenance of their systems as well as create, optimize, and run their HPC applications. Read more…

NERSC Simulations Shed Light on Fusion Reaction Turbulence

September 19, 2017

Understanding fusion reactions in detail – particularly plasma turbulence – is critical to the effort to bring fusion power to reality. Recent work including roughly 70 million hours of compute time at the National E Read more…

Exascale Computing Project Names Doug Kothe as Director

September 20, 2017

The Department of Energy’s Exascale Computing Project (ECP) has named Doug Kothe as its new director effective October 1. He replaces Paul Messina, who is s Read more…

Takeaways from the Milwaukee HPC User Forum

September 19, 2017

Milwaukee’s elegant Pfister Hotel hosted approximately 100 attendees for the 66th HPC User Forum (September 5-7, 2017). In the original home city of Pabst Blu Read more…

By Merle Giles

Kathy Yelick Charts the Promise and Progress of Exascale Science

September 15, 2017

On Friday, Sept. 8, Kathy Yelick of Lawrence Berkeley National Laboratory and the University of California, Berkeley, delivered the keynote address on “Breakt Read more…

By Tiffany Trader

DARPA Pledges Another $300 Million for Post-Moore’s Readiness

September 14, 2017

The Defense Advanced Research Projects Agency (DARPA) launched a giant funding effort to ensure the United States can sustain the pace of electronic innovation vital to both a flourishing economy and a secure military. Under the banner of the Electronics Resurgence Initiative (ERI), some $500-$800 million will be invested in post-Moore’s Law technologies. Read more…

By Tiffany Trader

IBM Breaks Ground for Complex Quantum Chemistry

September 14, 2017

IBM has reported the use of a novel algorithm to simulate BeH2 (beryllium-hydride) on a quantum computer. This is the largest molecule so far simulated on a quantum computer. The technique, which used six qubits of a seven-qubit system, is an important step forward and may suggest an approach to simulating ever larger molecules. Read more…

By John Russell

Cubes, Culture, and a New Challenge: Trish Damkroger Talks about Life at Intel—and Why HPC Matters More Than Ever

September 13, 2017

Trish Damkroger wasn’t looking to change jobs when she attended SC15 in Austin, Texas. Capping a 15-year career within Department of Energy (DOE) laboratories, she was acting Associate Director for Computation at Lawrence Livermore National Laboratory (LLNL). Her mission was to equip the lab’s scientists and research partners with resources that would advance their cutting-edge work... Read more…

By Jan Rowell

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

MIT-IBM Watson AI Lab Targets Algorithms, AI Physics

September 7, 2017

Investment continues to flow into artificial intelligence research, especially in key areas such as AI algorithms that promise to move the technology from speci Read more…

By George Leopold

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

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

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

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

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

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

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

Leading Solution Providers

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

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

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

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The Read more…

By John Russell

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

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