Big Red II Colors New Page for Hybrid Systems

By Nicole Hemsoth

April 19, 2013

Back in 1995, Thomas Sterling, along with academic comrades Paul Messina and Paul Smith collaborated on a forward-looking tome called, Enabling Technologies for Petaflops Computing, which explored a far-flung future that has finally arrived.

During a chat with Sterling this morning, the topic of the book cropped up, in part because the Indiana University professor (and notable luminary in Beowulf and thought leadership circles) has been biding his time until he could have a petaflopper to call his own—or at least one in cozy reaching distance at IU.

Later this month, Indiana University will formally introduce the successor to the Big Red system, the aptly-named, Big Red II. The Cray-crafted and tuned system is 25 times faster than its baby brother (the 4100-core original Big Red from 2006) and sports some notable improvements across its 1,020 nodes. With some Kepler spice and the snappy Gemini interconnect to push its peak one teraflop performance to an expected top 30 range for June’s list, the system will aim its big guns at true “big data” problems.

IU thinks some theoretical work on the “little” 210,000-core Big Red II can unleash some optimization dragons for systems like Titan and Blue Waters to ride, at least in theory. With a common, mixed-up architecture that is either homogeneous or heterogeneous, depending on how it’s feeling for particular applications, there are significant opportunities to fine-tune core operations to take best advantage of any configuration.

What’s needed for such systems is an execution model that can self-adapt on non-uniform systems. And since it’s the same big idea on a smaller canvas (than Titan and Blue Waters), Sterling said he has hope that tweaking the ParalleX execution model could yield some big returns.

Although Big Red II is far smaller than Titan or Blue Waters, it’s the same technology, architecture and software environment than its big hybrid peers—and this triad of features is likely to be at the top of the trend list for new systems in the coming years.

On that note, Sterling was in the midst of a trip this week to Sandia National Lab (both part of the XPRESS project) to talk about Big Red II and these experimental pieces of a potential programming model and runtime system that might play nicely with such unique, hybrid supers. There are obvious architectural similarities between big boy systems like Titan and Blue Waters, and the Hoosiers have hopes that Big Red II can help create a playbook for similar system operators to score maximum performance, scalability and of course, efficiency out of their supers.

There are a few things that Sterling and his many counterparts expect from Big Red, including counting on its iron hand to help shove some new ideas about using these trend-setting systems efficiently and at massive scale. “The trick is to address the challenges of asynchrony and compensate for that uncertainty. That’s what our runtime system will demonstrate, or so we hope—at least for some applications on Cray systems like the one we have now.”

The other proof pudding they hope to whip up at IU relates to tackling new classes of data-intensive problems that are memory-bound, exploit locality and move beyond traditional numerically-oriented approaches. We need to move back toward an older concept that never enjoyed its day in the sun, argues Sterling—we need to think back to the promise of symbolic computing and how systems like Big Red and others can turn the standard model on end. Overused buzzword or not, this is all about “big data,” a topic that can’t be shoved under the HPC rug as a trend when it’s already influencing the shift toward Titan-esque systems.

On the big data front, Sterling and his team at IU, under the university’s VP of IT and CIO, Brad Wheeler, set about driving stakes in new supercomputing ground, the emphasis was on pushing performance. But just as important as floating point was the need to make critical decisions about memory. He pointed to a number of people at IU that helped make core decisions, and also to Bill Blake from Cray who helped them refine and tweak to perfection.

Sterling notes that in terms of system design (full specs here), the choice to snap in AMD Interlagos and Abu Dhabi processors wasn’t an Intel versus AMD decision, it was “purely generational” for this pre-Intel Cray design. The Kepler cores were a key investment since, as Sterling described, there are “many science codes that, with sufficient refactoring, could take advantage of GPUS.” He said, “It doesn’t mean it’s easy, but under the right circumstances, we’re looking at a 5x to 10x speedup.” This is going to boost their production capabilities to new levels, he notes, and is aided by the fact that Geoffrey Fox and other critical folks at IU were pushing fresh envelopes on the GPU and parallel computing fronts before this Kepler-sporting system landed on their datacenter doorstep to begin with.

In terms of extracting ultra performance on a system designed with data-intensive problems in mind, Sterling said there is a balance between FLOPS and big data considerations, including laying down memory foundations and keeping data and compute at the end of the same stick. “The importance of FLOPS will continue to grow,” he notes, “but the importance of big data and knowledge analytics will grow faster.”

 “It’s the symbolic graph structures and future architectures we need to make computers understand its data, not just manipulate…right now, that’s a big constraint. The work on Big Red II will let us move closer to knowledge, knowledge management and most importantly, machine understanding of knowledge and that will change how we pursue problems in climate change, drug design, very complex system design as in large aircraft that doesn’t take decades–but weeks or less.”

 “Computers manipulate data and take action on it. Human beings manipulate knowledge and make that actionable and there’s a gap between data and knowledge. We don’t want big data—we want smart knowledge. And that’s where the research has to be and that’s how the usage patterns of big computers need to reflect.”

Whether or not “big data” is just a new term for wrapping HPC around a new architecture that’s optimized for certain applications or problems, it’s a term that has staying power, even for the self-confessed “hype hater” Sterling. But at the end of the day, for the guy who helped write the book on what petascale systems would be made of, Sterling says that “here so many years later, I’m finally getting my hands on [a system]. It’s closure in my career and truly an exciting time.”

Related Articles

IU’s Big Red II Supercomputer Being Dedicated on April 26

IU Data Capacitor II Joins Big Red Supercomputer II

Indiana University to Deploy Petascale Cluster

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!

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

IDC: Will the Real Exascale Race Please Stand Up?

February 21, 2017

So the exascale race is on. And lots of organizations are in the pack. Government announcements from the US, China, India, Japan, and the EU indicate that they are working hard to make it happen – some sooner, some later. Read more…

By Bob Sorensen, IDC

ExxonMobil, NCSA, Cray Scale Reservoir Simulation to 700,000+ Processors

February 17, 2017

In a scaling breakthrough for oil and gas discovery, ExxonMobil geoscientists report they have harnessed the power of 717,000 processors – the equivalent of 22,000 32-processor computers – to run complex oil and gas reservoir simulation models. Read more…

By Doug Black

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

O&G Companies Create Value with High Performance Remote Visualization

Today’s oil and gas (O&G) companies are striving to process datasets that have become not only tremendously large, but extremely complex. And the larger that data becomes, the harder it is to move and analyze it – particularly with a workforce that could be distributed between drilling sites, offshore rigs, and remote offices. Read more…

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Drug Developers Use Google Cloud HPC in the Fight Against ALS

February 16, 2017

Within the haystack of a lethal disease such as ALS (amyotrophic lateral sclerosis / Lou Gehrig’s Disease) there exists, somewhere, the needle that will pierce this therapy-resistant affliction. Read more…

By Doug Black

Weekly Twitter Roundup (Feb. 16, 2017)

February 16, 2017

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

Alexander Named Dep. Dir. of Brookhaven Computational Initiative

February 15, 2017

Francis Alexander, a physicist with extensive management and leadership experience in computational science research, has been named Deputy Director of the Computational Science Initiative at the U.S. Read more…

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

IDC: Will the Real Exascale Race Please Stand Up?

February 21, 2017

So the exascale race is on. And lots of organizations are in the pack. Government announcements from the US, China, India, Japan, and the EU indicate that they are working hard to make it happen – some sooner, some later. Read more…

By Bob Sorensen, IDC

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Drug Developers Use Google Cloud HPC in the Fight Against ALS

February 16, 2017

Within the haystack of a lethal disease such as ALS (amyotrophic lateral sclerosis / Lou Gehrig’s Disease) there exists, somewhere, the needle that will pierce this therapy-resistant affliction. Read more…

By Doug Black

Azure Edges AWS in Linpack Benchmark Study

February 15, 2017

The “when will clouds be ready for HPC” question has ebbed and flowed for years. Read more…

By John Russell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Cray Posts Best-Ever Quarter, Visibility Still Limited

February 10, 2017

On its Wednesday earnings call, Cray announced the largest revenue quarter in the company’s history and the second-highest revenue year. Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

US, China Vie for Supercomputing Supremacy

November 14, 2016

The 48th edition of the TOP500 list is fresh off the presses and while there is no new number one system, as previously teased by China, there are a number of notable entrants from the US and around the world and significant trends to report on. Read more…

By Tiffany Trader

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

D-Wave SC16 Update: What’s Bo Ewald Saying These Days

November 18, 2016

Tucked in a back section of the SC16 exhibit hall, quantum computing pioneer D-Wave has been talking up its new 2000-qubit processor announced in September. Forget for a moment the criticism sometimes aimed at D-Wave. This small Canadian company has sold several machines including, for example, ones to Lockheed and NASA, and has worked with Google on mapping machine learning problems to quantum computing. In July Los Alamos National Laboratory took possession of a 1000-quibit D-Wave 2X system that LANL ordered a year ago around the time of SC15. Read more…

By John Russell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

Leading Solution Providers

Nvidia Sees Bright Future for AI Supercomputing

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Read more…

By Tiffany Trader

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

Dell Knights Landing Machine Sets New STAC Records

November 2, 2016

The Securities Technology Analysis Center, commonly known as STAC, has released a new report characterizing the performance of the Knight Landing-based Dell PowerEdge C6320p server on the STAC-A2 benchmarking suite, widely used by the financial services industry to test and evaluate computing platforms. The Dell machine has set new records for both the baseline Greeks benchmark and the large Greeks benchmark. Read more…

By Tiffany Trader

What Knights Landing Is Not

June 18, 2016

As we get ready to launch the newest member of the Intel Xeon Phi family, code named Knights Landing, it is natural that there be some questions and potentially some confusion. Read more…

By James Reinders, Intel

KNUPATH Hermosa-based Commercial Boards Expected in Q1 2017

December 15, 2016

Last June tech start-up KnuEdge emerged from stealth mode to begin spreading the word about its new processor and fabric technology that’s been roughly a decade in the making. Read more…

By John Russell

Intel and Trump Announce $7B for Fab 42 Targeting 7nm

February 8, 2017

In what may be an attempt by President Trump to reset his turbulent relationship with the high tech industry, he and Intel CEO Brian Krzanich today announced plans to invest more than $7 billion to complete Fab 42. Read more…

By John Russell

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