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 industry updates delivered to you every week!

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

Nvidia Appoints Andy Grant as EMEA Director of Supercomputing, Higher Education, and AI

March 22, 2024

Nvidia recently appointed Andy Grant as Director, Supercomputing, Higher Education, and AI for Europe, the Middle East, and Africa (EMEA). With over 25 years of high-performance computing (HPC) experience, Grant brings a Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

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

March 18, 2024

Nvidia's latest and fastest GPU, codenamed 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…

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…

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…

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…

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…

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…

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

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…

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…

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…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire